UNIVERSITY OF CALIFORNIA, LOS ANGELESUniversity of California-Los AngelesSeth G Claudepierre(303) 641-2461seth.claudepierre@gmail.com09/21/2018$64,446$64,44608/01/201807/31/2019GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: GEM--The Effect of Magnetosonic Waves on Energetic Electrons in the Earth's Magnetosphere1854440092530369071549000MAGNETOSPHERIC PHYSICSCarrie E. Black(703) 292-8519cblack@nsf.gov10889 Wilshire BoulevardLOS ANGELESCA90095-1406Los AngelesUS33University of California-Los AngelesCA90095-1406Los AngelesUS33This project aims to address the electromagnetic waves in Earth's magnetic field (magnetosphere) on charged particles, electrons specifically. This work is timely and highly relevant for improving the modeling and prediction of radiation belt electrons, which are of considerable practical importance due to their potential hazards to space systems. Specifically, radiation hazards have damaging effects on spacecraft through surface and internal charging. The research is directed towards advancing our understanding of the fundamental physical processes in the inner magnetosphere and dynamics of the radiation belt. The results will be utilized to improve current radiation belt modeling capabilities. This project also supports two early career scientists and a doctoral student. The findings of this project will be incorporated into a new introductory course in magnetospheric physics that the lead Principal Investigator is developing at University of Texas-Dallas .
This project is a unified investigation, taking advantage of both observations and modeling, to quantify the effect of equatorial magnetosonic (MS) waves on energetic electron dynamics in the inner magnetosphere. MS waves have gained an increasing amount of attention in the research community, due to their potential mechanism for electron acceleration via Landau resonance, and their scattering of equatorially mirroring electron via bounce resonance. Recent Van Allen Probes observations have revealed the formation of electron butterfly distributions associated with MS waves, and in-situ modulation of the electron pitch angle distribution by the MS waves. The dynamics of equatorially mirroring electrons is important scientific question, which currently is not implemented in radiation belt models. This project will address the three fundamental scientific questions: What is the relation between MS waves and the electron butterfly pitch angle distribution in the inner magnetosphere? How do electron transport coefficients depend on magnetosonic wave normal and wave spectra and background plasma parameters? And how can bounce resonance effects be incorporated into models? To address these questions, high-resolution wave and particle measurements from the twin Van Allen Probes will be analyzed. Test particle simulations will be carried out to calculate the electron transport coefficients as a function of pitch angle and energy, and then perform a parametric study of those transport coefficients. Phase space density evolution due to MS waves will be modelled and compared with high-resolution electron pitch angle distributions from Van Allen Probes.UNIVERSITY OF WASHINGTONUniversity of WashingtonMo Li(612) 638-8958moli96@uw.edu09/21/2018$149,665$149,66509/01/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Conformal and robust integrated infrared spectroscopic sensors1854974605799469042803536COMMS, CIRCUITS & SENS SYSShubhra Gangopadhyay(703) 292-2485sgangopa@nsf.gov4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07University of WashingtonWA98195-0001SeattleUS07The program aims to pioneer a flexible optical sensor which can be conformally attached to human skin for continuous physiological monitoring. Unlike conventional optical sensors which are often bulky, costly, and involve mechanical moving parts which compromise their robustness, the proposed effort will leverage advanced integrated photonic technologies to combine miniaturized optical components on a flexible polymer membrane. The proposed sensor is ideally suited for continuous glucose monitoring. Instead of relying on fingertip pricking with lancets to draw blood for intermittent analysis, the proposed sensor will assume a minimally invasive, tattoo-like form factor for continuous monitoring of glucose concentration in body fluids.
Integrated photonic devices are uniquely poised for in-vivo sensing, diagnostics, therapeutics, and stimulation functions, given their small form factor, low power consumption, robustness, large multiplexing capacity, as well as strong light-molecule/tissue interactions enabled by tight optical confinement in these devices. Nevertheless, conventional photonic integration is predominantly based on rigid semiconductor substrates, and their mechanical stiffness makes the resulting devices inherently incompatible with soft biological tissues. Further, while optical spectroscopy based on bench top instruments has become the gold standard in analytical chemistry, integrated spectroscopic sensors remain largely unexplored. This program aims to resolve the challenges by combining flexible photonic integration and on-chip infrared spectroscopic sensing technologies to pioneer a wearable photonic sensing system on conformal plastic substrates. Specifically, a minimally invasive epidermal sensor for continuous glucose monitoring will be demonstrated as a proof-of-concept model platform. The two-fold intellectual merits of the program lie in the unconventional multi-material photonic integration approach on conformal substrates as well as the innovative spectroscopic sensor design. Photonic integration on conformal substrates poses a diverse set of often mutually conflicting requirements on the mechanical and optical properties of constituent materials. In this program, a transformative multi-material, multi-functional integration approach on flexible substrates will be pursued where each material is seamlessly integrated into the process flow and strategically shaped and positioned so as to make use of its advantageous properties while circumventing its limitations. On the spectroscopic sensing front, miniaturization and integration of spectrometers present a major technical barrier towards spectroscopic sensor integration onto chip-scale platforms. Rather than downscaling traditional spectrometers, the program will develop a novel sensor design with significantly improved system simplicity, ruggedness, reproducibility and specificity, enabling wearable sensing applications. The scientific research will be tightly integrated with curriculum development, undergraduate student training, and development of hands-on modules for optics education. In addition to augmenting classroom education at both institutes, the program will promote the free sharing and distribution of knowledge by developing online courses through the MIT OpenCourseWare and edX initiatives.CLEMSON UNIVERSITYClemson UniversityYongjia Song(864) 656-9832yongjis@clemson.edu09/21/2018$84,855$84,85509/01/201805/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITAn Adaptive Partition-based Approach for Solving Large-Scale Stochastic Programs1854960042629816042629816OE Operations EngineeringGeorgia-Ann Klutke(703) 292-8360gaklutke@nsf.gov230 Kappa StreetCLEMSONSC29634-5701US03Clemson University230 Kappa StreetClemsonSC29634-0001ClemsonUS03Stochastic programs are popular models for problems requiring optimization under uncertainty. Stochastic programs are challenging to solve, especially when uncertainty characterization relies on a large number of scenarios. Consequently, both scenario decomposition and scenario reduction (clustering and aggregation) techniques are used to reduce computational burden. The latter are performed either in a heuristic manner, or in a way that does not utilize information from intermediate solutions. This project's objective is to advance a computational framework based on partitioning the scenario set adaptively during the solution process. If successful, the technique can be potentially integrated into existing algorithms and software. By enabling faster computation, and in some cases making it possible to solve larger problem instances, the project has the potential to impact a whole host of applications requiring optimization under uncertainty.
The adaptive partition-based framework will provide a mechanism to aggregate information from scenario sub-problems, by replacing the entire scenario set with an adaptively constructed partition of scenarios. If successful, this will lead to an algorithmic way to coordinate the efforts between approximating the distribution and optimization. The approach will integrate both the optimal (static) scenario reduction technique and the regularized cutting-plane method with inexact oracles in the context of stochastic programs. The developed algorithms will address two-stage and multi-stage stochastic linear programs as well as stochastic integer programs.TEXAS A&M ENGINEERING EXPERIMENT STATIONTexas A&M Engineering Experiment StationYa Wang(631) 632-8322ya.s.wang@stonybrook.edu09/21/2018$500,000$500,00009/01/201807/31/2023GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCAREER: Understanding Dynamics of Ultra-small Magnetic Nanoparticles in the Brain for Neuron Regeneration Therapies1851635847205572847205572Dynamics, Control and System DIrina Dolinskaya(703) 292-7078idolinsk@nsf.govTEES State Headquarters Bldg.College StationTX77845-4645College StationUS17Texas A&M UniversityCollege StationTX77843-3578College StationUS17This Faculty Early Career Development Program (CAREER) project will create new understanding of an innovative treatment for neurodegenerative diseases (i.e., Alzheimer's and Parkinson's) and promote the progress of science and advance the national health. Neurodegenerative disease, resulting from the progressive loss of neurons, takes a devastating toll on the aging population in the U.S. Recent advances in magnetically driven biodegradable ultra-small nanoparticles offer opportunities in transformational non-invasive neuron regeneration treatments. This innovative technology holds great potential to usher biotechnology into a new era of precision medicine and tissue engineering. However, to date, neuroscientists have largely focused on the associated biological phenomena, with little attention to microvascular dynamics of nanoparticle transport, thus limiting the translation to clinical practice. The microvascular dynamic model, established from this research will be capable of quantifying the neuron regeneration process. This is essential for overcoming intrinsic trial-and-error approaches and for moving closer to clinical success. Additionally, the education and outreach activities of the project will advance awareness of nanotechnology and biomedicine, and will increase the participation of historically underrepresented groups in STEM, including women, and first-generation college students in the greater Long Island.
The research objective of this CAREER project is to employ analytical perturbative and continuation approaches to analyze biological phenomena to yield a rich harvest of predictive insights into the microvascular dynamics of ultra-small nanoparticles transport in a brain microenvironment. The research plan is to first create two dynamic models: one will capture the magnetic transport behavior of ultra-small nanoparticles within a microvasculature; the other will describe cytoskeleton dynamics within brain microvascular networks. Combined, a microvascular dynamic model of nanoparticle transport will be established to discern which parameters are needed for directing target-selective magnetic stimulation to produce a reliable and steady therapeutic tool by applying a pre-defined magnetic field on the nanoparticles. For the first time, cytoskeleton dynamics associated with growing neurons will be analyticaly modeled by perturbing a nanoparticle diffusing in a potential well with a slowly drifting minimum position. Importantly, this model will be constructed to track the individual growing behaviors of thousands of neurons, and perform high-throughput/low-cost sensitivity analyses to identify the key parameters in a complex brain microenvironment. Furthermore, combined with recent advances in power electronics, this project holds a high potential for contributing to the development of a new microchip that improves researcher capacity for studying the growth behavior of the neuron cells inside a three dimensional extracellular matrix.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF PITTSBURGH THEUniversity of PittsburghMasoud Barati(225) 578-1054mbarati@lsu.edu09/21/2018$199,893$199,89308/28/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: A Global Algorithm for Quadratic Nonconvex AC-OPF Based on Successive Linear Optimization and Convex Relaxation1851602004514360004514360ENERGY,POWER,ADAPTIVE SYSAnil Pahwa(703) 292-2285apahwa@nsf.govUniversity ClubPittsburghPA15213-2303PittsburghUS14University of PittsburghPittsburghPA15213-2303PittsburghUS14Non-convex programming involves optimization problems where either the objective function or constraint set is a non-convex function. These kinds of problems arise in a broad range of applications in engineering systems. Despite the substantial literature on convex and non-convex quadratic programming (general classes of optimization problems), most available optimization techniques are either not scalable or work efficiently only for convex quadratic programming and do not provide adequate results for non-convex quadratic programming. This project focuses on fundamental research on an integrated approach which the research team expects will lead to powerful solution methods for classes of non-convex programming problems. The new approach will be applicable for non-convex problems arising in many areas, such as power and energy systems, transportation, and communications. The project will involve students from underrepresented groups and will positively impact engineering education.
The general difficulty of power and energy optimization problems has a direct impact on power and energy systems management. This is one of the most fundamental concerns that must be dealt with in electrical power system management. The primary objective of this project is to address the difficulty associated with problem non-convexity by developing high-performance optimization techniques that apply to a broad set of nonlinear energy problems, particularly the Optimal Power Flow (OPF) problem. There is a critical and urgent need for developing smart and robust OPF solvers. The conventional options currently available for DC-OPF are quite limited. The research will fundamentally address AC Optimal Power Flow (AC-OPF) with active and reactive quadratically constrained quadratic programming optimization problems of a form that arises in operation and planning applications of the power system. Besides being non-convex, these problems are identified to be NP-hard. The proposed solution method is based on several basic and powerful optimization techniques in convex optimization theory such as linearized approximation techniques, linear and global search procedures, bi-linear and convex relaxation, and alternate direction methods. Also, new schemes and theories must be introduced to establish the convergence of the algorithm and guarantee the global optimality of the solution results. The research team devised a new successive linear optimization based branch and bound (SLOBB) method based on deploying principles of the classical linear approximation, improved convex relaxation, and the branch-and-bound technique to find the global optimal solution of the AC-OPF problem. Since the linear programming and convex solvers are robust and fast, and also the power systems community is already familiar with linear and convex programs for OPF, the algorithm that will be developed will be beneficial and user-friendly for the AC-OPF problem. We will also pursue theoretical investigations to examine the performance of the proposed algorithm and analyze its efficiency on existing test bed systems and synthetic data sets. The developed models and methodologies will be executed in real-world practical power grids.UNIVERSITY OF TEXAS AT ARLINGTONUniversity of Texas at ArlingtonMing Li(775) 682-6861mingli@unr.edu09/21/2018$134,774$134,77408/21/201806/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCCSS: Collaborative Research: Towards Privacy-Preserving Mobile Crowd Sensing: A Multi-Stage Solution1849860064234610042000273COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov701 S Nedderman Dr, Box 19145ArlingtonTX76019-0145ArlingtonUS06University of Texas at ArlingtonTX76019-0145ArlingtonUS06Mobile devices, including smartphones and tablets, are becoming extremely prevalent nowadays. Equipped with diverse sensors, from GPS to camera, and paired with the inherent mobility of their owners, mobile devices are capable of acquiring rich information of surrounding environment. However, the wide adoption of mobile crowd sensing is largely hindered by its privacy concerns. To facilitate the functionality of each stage of mobile crowd sensing, including sensing task allocation, sensing data collection, and result aggregation, sensing devices report their location information, sensing capabilities, task preferences, and sensing results to servers that will potentially disclose their daily routings, behavior patterns and even identities. With these concerns, the overall goal of this project is to address privacy leakage issues from different stages of mobile crowd sensing. Privacy-enhanced mobile crowd sensing will attract more participants and thus accelerate the maturity of smart health care, environment monitoring, traffic surveillance, social event observation, etc. In addition, this project will also serve as a training ground for educating future decision-makers and workforce on theory and tools.
The PIs plan to develop effective and efficient privacy preservation schemes for different stages of mobile crowd sensing. It corresponds to three closely intertwined research thrusts. Thrust I explores protecting user's sensitive information, such as locations, sensing capabilities and task preferences, from the server, while still allowing it to optimally or approximately solve task allocation problems. Rather than highly computationally-intensive crypto-based techniques, privacy preservation schemes will be designed based on decomposition methods and distributed computing algorithms. Thrust II aims to provide user's location privacy in the stage of data collection. Since locations of users, who perform sensing over the same event within a certain geographic area, are highly correlated, it deteriorates user's privacy achieved individually. To address this issue, privacy preservation schemes will be developed by exploring collaborations among users. Game theories will be adopted to further analyze users' strategies and interactions. The objective of Thrust III is to protect users' sensing data privacy during the stage of data analysis. The research is featured by jointly considering the data imperfection that is caused by the limited sensing capabilities at mobile devices and even the misbehavior of lazy/malicious users. To achieve data privacy and service accuracy simultaneously, novel schemes will be developed combining efficient matrix completion methods and advanced crypto techniques.MORGAN STATE UNIVERSITYMorgan State UniversityKofi Nyarko(443) 885-3476Kofi.Nyarko@morgan.eduJohn Attia, Petru Andrei, Shujun Yang, Sacharia Albin09/21/2018$2,333,172$781,23510/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITREU-RET Mega-Site: Research Experiences for Undergraduates and Teachers in Smart and Connected Cities1849454879941318879941318HUMAN RESOURCES DEVELOPMENTMary Poats(703) 292-5357mpoats@nsf.gov1700 East Cold Spring LaneBaltimoreMD21251-0002BaltimoreUS07Morgan State University1700 E. Cold Spring LaneBaltimoreMD21251-0002BaltimoreUS07The goal of this project, REU-RET Mega-Site: Research Experiences for Undergraduates and Teachers in Smart and Connected Cities (led by Morgan State University), is to recruit and train a diverse population of underrepresented minority students and teachers who work in minority-serving K-12 schools and community colleges - focusing on highly relevant Electrical and Computer Engineering research topics. The project involves the development of a combined Research Experiences for Undergraduates and Research Experiences for Teachers (REU-RET) Mega-Site that is centered on the following research topics that are related to Smart and Connected Cities: IoT Security, Renewable Energy, Energy Storage, Smart Grid, Human Computer Interaction, and Advanced Materials. The consortium of institutions involved in this effort are 14 Historically Black Colleges and Universities (HBCUs) and 1 Hispanic Serving Institution (HSI). The project targets lower division students who are less likely to have the opportunity to participate in research as undergraduates. Participation in this type of experience has been demonstrated to be transformative and to have the potential to increase retention and graduation rates at these institutions. RET participants will be recruited from local community colleges and high schools that serve as feeder schools to the consortium institutions.
Providing quality research experiences to an underserved group of undergraduate students and teachers will lay the foundation for positively impacting the retention and graduation of engineering students for years to come, while also increasing the number of minority students who will eventually pursue graduate degrees. In addition, the program will improve the quality of science and engineering education at local high schools and community colleges, further stimulating the interest and imagination of underrepresented minority students who might not otherwise be inclined to pursue higher education in Science, Technology, Engineering, and Mathematics (STEM) fields. The project will serve as a national model for how to broaden participation in engineering by successfully implementing multi-institution undergraduate research programs, which others can adopt/adapt and build upon. The evaluation of this effort will be conducted by the SageFox Consulting Group and the project's outcomes will be broadly disseminated through Morgan State University's website, presentations at conferences, and articles that are published in peer-reviewed journals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ASSOCIATION OF UNIVERSITIES FOR RESEARCH IN ASTRONOMY, INC.Association of Universities for Research in Astronomy, Inc.Charles Mattias Mountain(202) 483-2101nsfnotifications@aura-astronomy.orgRobert D Blum09/21/2018$11,100,000$11,100,00010/01/201809/30/2021Cooperative AgreementsNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITPre-Operations of the Large Synoptic Survey Telescope (LSST)1836783057905887057905887LSSTEdward Ajhar(703) 292-7456eajhar@nsf.gov1331 Pennsylvania Ave. NWWashingtonDC20004-0000US00Association of Universities for Research in Astronomy, Inc.950 N Cherry AvenueTucsonAZ85719-4933TucsonUS03The Large Synoptic Survey Telescope (LSST) is not just another telescope, but a new approach to survey science and data-based astronomy. Existing 6-meter to 10-meter ground-based telescopes all have relatively small fields of view and are operated in the traditional mode where a given project is pursued for a few nights at a time, after which different astronomers pursue data addressing a different scientific goal, possibly with a different instrument. Although this approach can make great advances, there are some crucial scientific problems that need to be tackled more like a physics experiment, whereby a dedicated instrument is used for a finite period of time to address well-defined objectives. This is LSST: a large survey telescope using a wide field camera to image the accessible sky repeatedly to very faint limits over a ten-year period. The LSST data products will change every field of astronomical study, from the inner Solar System to the large scale structure of the Universe.
LSST will map the inner and outer Solar System, study stellar populations in the Milky Way and nearby galaxies, reveal the structure of the Milky Way disk and halo and other local objects, find transient and variable objects at both low and high redshift, and survey the properties of normal and active galaxies at low and high redshift. Turning to far-field cosmological topics, LSST will explore the properties of supernovae to redshifts around one, uncover strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and show how these different probes may be combined to constrain cosmological models and the physics of dark energy.
LSST is being built on the El Penon peak on Cerro Pachon in northern Chile. LSST will have a unique primary-tertiary mirror of 8.4-meter diameter with an effective aperture of 6.7 meters and an imaging camera with field of view 9.6 square degrees, and will be devoted to a ten-year imaging survey over 20,000 square degrees south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands at wavelengths from 0.35 to 1.1 micrometers, to a total point-source depth of r ~ 27.5 magnitudes. LSST's three large mirrors are actively controlled to minimize distortion, and the telescope structure is especially compact and stiff to reduce image motion and to enable rapid travel across the sky, maximizing the observing duty cycle. The project is an interagency public-private partnership, with the Department of Energy accepting responsibility for the world-leading camera, while NSF as overall lead agency will support the site facility, the telescope, and the extensive and sophisticated data management. Private donations have supported initial construction work that significantly reduces project risk, including the innovative primary-tertiary mirror, early site work, and development of sensors for the camera. LSST will produce on average 15 terabytes of raw data per night and an uncompressed data set for the full ten-year survey of some 200 petabytes. Dedicated facilities will process the image data in near real time.
The image archive and resulting catalogs will be widely and freely available. A sophisticated data management system will enable work ranging from simple queries from individual users to computationally intensive scientific investigations that could use the entire data set. The LSST Project is at the forefront of the information technology revolution and includes investments in technology, cyber-infrastructure, education, and outreach. With one of the largest scientific databases in existence, the LSST project presents challenging opportunities for research into database architecture and data mining. Education and public outreach programs are fully integrated with the research program and include engaging experiences for non-specialists, partnerships with museums, schools, and industry, and opportunities to challenge and encourage tomorrow's innovators.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF KENTUCKYUniversity of Kentucky Research FoundationDan M Ionel(859) 257-9420dan.ionel@uky.eduAaron M Cramer09/21/2018$375,214$375,21410/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITNovel Ultra-high Polarity and High-frequency Axial Flux Electric Machines and Wide Band Gap Power Electronic Drives1809876939017877007400724ENERGY,POWER,ADAPTIVE SYSRadhakisan S. Baheti(703) 292-8339rbaheti@nsf.gov109 Kinkead HallLexingtonKY40526-0001LexingtonUS06University of Kentucky Research Foundation500 S Limestone 109 Kinkead HallLexingtonKY40526-0001LexingtonUS06Electric motors account for more than 60% of the electricity consumed and electric machines and associated power electronic drives represent a multi-billion dollar industry. The research will develop fundamental knowledge and innovative concepts for high-efficiency and high-performance electric machines and drives through a synergetic combination of transformational designs, multiphysics analysis, and the latest developments in power electronics, including wide band gap devices. The project will train graduate and undergraduate research students, lead to engineering teaching and training curriculum development, publically disseminate the results, and support STEM middle and high school outreach activities and increased efforts to attract students, including women and minorities, to higher education in science and engineering.
Raising the fundamental operating frequency for electrical machines results, in principle, in increased power density, provided that the typical challenges of higher losses, lower material utilization, and more complicated constructions, which are specific to conventional designs, can be overcome. The research will provide innovative solutions in this respect and study two novel axial flux permanent magnet machine topologies, which are best fitted for ultra-high number of poles and operation with high fundamental frequency, ensured through controlled supply from power electronics with wide band gap devices. One construction, suitable for high-speed operation, employs a coreless stator with an innovative continuous-wave phase winding arrangement in multiple layers. Another construction, suitable for low-speed direct drive operation, employs special rotors and innovative ferromagnetic-core stators with a winding pattern such that the stator coils and teeth are one order of magnitude lower than the number of rotor poles, a design feature that far exceeds the characteristics of known topologies. This machine also incorporates a torque magnification effect, which contributes to size reduction and efficiency increase for given power output. For two-phase machine designs, innovative hybrid H-bridge inverters comprising one leg with wide band gap devices and another leg with silicon devices are proposed for control and system integration. Computational studies include multi-physics analysis for electromagnetic, thermal, and mechanical stress, and differential evolutionary algorithms for mathematical optimization, and systematic comparison of thousands of candidate designs. Experimental studies include building prototype demonstrators and laboratory testing. The outcomes are ultra-high power density and efficient electric machine - drive systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.FLORIDA INTERNATIONAL UNIVERSITYFlorida International UniversityHabarakada Madanayake(330) 957-8704amadanay@fiu.edu09/21/2018$152,246$152,24607/25/201807/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSpecEES: Collaborative Research: Spatially Oversampled Dense Multi-Beam Millimeter-Wave Communications for Exponentially Increased Energy-Efficiency1854798071298814159621697SpecEES Spectrum Efficiency, EJenshan Lin(703) 292-7950jenlin@nsf.gov11200 SW 8TH STMiamiFL33199-0001MiamiUS26Florida International University11200 SW 8th StreetMiamiFL33199-0001MiamiUS26The vast amount of spectrum available in the millimeter-wave (mmW) bands offer a path for exponential growth in data rates for wireless communications networks. In emerging systems such as fifth-generation (5G) networks, the use of mmW frequencies will potentially enable unprecedented improvements in network capacity, mobility, and spectral efficiency. However, the exploitation of mmW bands requires solutions to many technical challenges. In particular, the technology limitations present in today's implementations require new paradigms in algorithms, signal processing methods, circuit architectures, and integration methods in order for 5G wireless to become a reality. For example, there is a need for advanced channel models that let designers implement the wireless network infrastructure of the future. There is also a need for new algorithms, software, hardware, and electronic circuits for efficient mmW antenna array processing. This project will exploit well-known physics arising from Einstein's Special Theory of Relativity, namely the causality light-cone, to significantly improve the performance of key array signal processing components in mmW wireless basestations. Specifically, the spatio-temporal properties of electromagnetic waves, as described by Special Relativity, are exploited in novel architectures to improve the energy efficiency, reduce the noise, and improve the linearity of array receivers. A system-wide study of spatio-temporal properties of mmW channels is combined with these architectures to design new types of mmW array receivers and optimum beam forming algorithms.
The Special Theory of Relativity describes a region in the multidimensional spacetime continuum that is not occupied by propagating waves due to the constant speed of light and the nature of the wave equation. As a result, the region of support (ROS) of all propagating waves, which correspond to wireless propagation channels, are confined inside a ``Light Cone''. The region of spacetime outside this cone (known as ``Elsewhere'') is a void within which wireless communications signals cannot propagate. Although devoid of waves, the Elsewhere is occupied by both electronic noise and nonlinear distortion arising from real-world amplifiers and data converters. The project explores the possibility of spatially over-sampling the mmW antenna arrays and thereafter applying multidimensional extensions of well-known sigma-delta modulation techniques across both discrete space and continuous-time dimensions to achieve noise and distortion shaping, which effectively move the unwanted received components into Elsewhere. Although sigma-delta algorithms have been employed in analog-to-digital converters (ADCs), it is here proposed that multidimensional extensions of these algorithms are not limited to just ADCs; rather, it is possible to apply these algorithms to low-noise amplifiers, ADCs and other circuit components used in arrays, which in turn leads to the creation of new concepts in multi-dimensional circuit theory for array processing. The technique is expected to lead to improved amplifier noise figure and linearity and exponentially improved ADC figure-of-merit for array digitization at a linear cost in the number of antennas and receivers. The resulting mmW array processors have applications in wireless communications, phased-array radar, and radio telescope antenna apertures. The project is a multi-institutional collaboration between four universities in Ohio and New York, and has multiple education and community outreach activities, which will be implemented via the annual Brooklyn 5G Summit. The project includes mentoring for female engineers and students, development of new educational material, and engagement of underrepresented groups in wireless communications topics. Outreach will be achieved through community activities, workshops, the Brooklyn 5G Summit including events for women in 5G, and scientific outreach and academic events organized within IEEE conferences. The mmW circuits research and education program combines theory with hands-on system prototyping. Industry engagement, which is critically important for emerging wireless technologies, is planned throughout the project, and facilitated via the annual Brooklyn 5G Summit. Open source models, designs and prototype chips will be offered to the public and wireless industry.UNIVERSITY OF WASHINGTONUniversity of WashingtonWei Cheng(253) 692-5860uwcheng@uw.edu09/21/2018$100,000$100,00009/01/201808/31/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCyberTraining: CIP: Collaborative Research: Enhancing Mobile Security Education by Creating Eureka Experiences1853982605799469042803536CyberTraining - Training-basedchun-hsi huang(703) 292-7877chuang@nsf.gov4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07University of Washington4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07The rapid development and rollout of mobile infrastructure and applications not only bring convenience to people's daily lives, but also give birth to threats that can jeopardize each individual's privacy and national security. Therefore, it is critical to train and educate the future workforce on the fundamental aspects of mobile security relevant to advanced cyberinfrastructure, and to improve their ability to identify, prevent, and respond to emerging threats. This project designs and develops a wide variety of intriguing and challenging hands-on laboratories that aim to create Eureka Experiences in reference to the "aha!" moment of understanding a previously incomprehensible concept. Such an illuminating learning experience is created by incorporating Inquiry-Based Learning (IBL) activities to hands-on laboratories. Overall, this project meets the pressing and essential needs in the Computer Science and Information Technology curricula, has a strong impact on developing the future workforce' core competencies and preparedness in mobile security related to advanced cyberinfrastructure, and helps advance national security.
In this project, three types of hands-on laboratories are designed and developed: i) Exploratory; ii) Core; and, iii) Advanced. The primary purpose of exploratory labs is to spark the interests of high school and community college students from diverse backgrounds to pursue a career in cybersecurity in mobile ecosystems related to advanced cyberinfrastructure. Core labs help prepare both undergraduate and graduate students in STEM for productive cybersecurity careers by enabling enduring understanding of key security concepts and technologies through hands-on practice in an interactive setting. Advanced labs assist future research workforce development by not only introducing emerging security technologies and threats, but also inspiring student research in related fields. In addition, a universal lab platform that is affordable and flexible is designed and developed. This project helps develop core competencies in a number of areas relevant to advanced cyberinfrastructure including how to secure mobile devices and wireless systems, protect large scale and streaming data from mobile and other sources, ensure user privacy, and prevent intrusion. By engaging all stakeholders during the development process, this project increases the likelihood of wide adoption of the developed materials by academic and professional communities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ASSOCIATION OF UNIVERSITIES FOR RESEARCH IN ASTRONOMY, INC.Association of Universities for Research in Astronomy, Inc.Charles Mattias Mountain(202) 483-2101nsfnotifications@aura-astronomy.orgStephen M Pompea, Lori E Allen, William L Buckingham Jr09/21/2018$4,499,578$3,322,21510/01/201809/30/2023Cooperative AgreementsNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITWindows on the Universe Center for Astronomy Outreach (WUCAO)1839157057905887057905887NOAOJames Neff(703) 292-2475jneff@nsf.gov1331 Pennsylvania Ave. NWWashingtonDC20004-0000US00Association of Universities for Research in Astronomy, Inc.950 N Cherry AvenueTucsonAZ85719-4933TucsonUS03With this project, Kitt Peak National Observatory (KPNO) will transform the recently retired McMath-Pierce Solar Telescope into an astronomy visualization and presentation center. The newly renovated McMath-Pierce facility will be fully integrated with the existing Kitt Peak Visitor Center (KPVC) and the combined operation will be called the Windows on the Universe Center for Astronomy Outreach. Two astronomy data visualization systems -- Science On A Sphere (SOS) and GeoDome Digital Planetarium -- along with interactive exhibits and an astronomy classroom will be installed. Both GeoDome and SOS are equipped to take astronomical imagery and modify it for spherical or hemispherical projection. The images and animations developed at KPNO can be shared with other facilities employing both SOS and the GeoDome (currently over 225 such facilities worldwide). The goals of this project are to develop the International Astronomy Outreach Center (IAOC), run by KPVC, as a functioning, self-sustaining astronomy outreach center, and expand the focus of the programs to include all NSF-supported astronomy. The benefits of such a program include: 1) significantly improved capability of the KPVC to present more engaging astronomy-based experiences to onsite guests, and 2) extended reach beyond those who travel to Kitt Peak.
This project provides a new, cost-effective model for conversion of an outdated science facility to a self-supporting educational facility that communicates the process and results of modern astronomical research. The long history of major investment in the facility will continue to generate returns as the facility is preserved and transformed into a new 21st-century astronomy outreach center using research-based best practices in science visualization and communication. Using the Science On A Sphere (SOS) and GeoDome Digital Planetarium platforms, Kitt Peak gains a highly capable facility to serve its visitors in new ways, while all NSF-funded astronomy facilities gain new global exposure through astronomy visualizations to public audiences without major investments. The Center will acquire imagery from NSF-funded astronomy and astrophysics facilities from around the globe, and then transform those files into data sets for presentation on both SOS and the GeoDome, and for distribution to all so-equipped sites for immediate display. This enables a major expansion and enhancement of existing programs and the creation of new programs. Guests to KPNO will have a wider window on modern astronomy, and regional and Tribal schools will benefit from new STEM education experiences. Visitors to museums and parks elsewhere in the US and other countries will see astronomy results created in this new, far-reaching facility displayed in their SOS theaters and GeoDome planetaria. Finally, this project preserves a venerable and iconic solar telescope, which, although eclipsed by the new capabilities of the Daniel K. Inouye Solar Telescope, is useful for public education activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TETON COMPOSITESTeton CompositesAndrew Hansen(307) 760-9317andrew.hansen@tetoncomposites.com09/21/2018$739,183$739,18310/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Simulation for structural integrity of as manufactured 3D printed parts1829664080331042SMALL BUSINESS PHASE IIPeter Atherton(703) 292-8772patherto@nsf.gov1938 Harney StLaramieWY82072-0000US00Teton Composites1938 Harney St.LaramieWY82072-3037LaramieUS00The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project relates to the notion of distributed manufacturing using 3D printing, where structural parts may be manufactured onsite, meeting on-demand needs while eliminating transportation costs and inventory storage. Unique, one-off prints, such as may often occur in the medical industry are another virtue of 3D print technology. For these reasons, virtually every major US manufacturing industry is exploring avenues to utilize 3D printing. While 3D printing is unquestionably entering the mainstream of manufacturing technology, a glaring gap in advancing the industry is the simulation of the performance of an "as manufactured" part. A common question surrounding 3D print manufacturing today is: "How do I know if my part will perform as envisioned?" The proposed technology brings an industry leading software simulation to the product engineer and designer to answer this very question, enabling engineers to predict part performance, prior to attempting a build. The speed and simplicity of the software solution is transformative, accelerating the adoption of this disruptive manufacturing technology.
This Small Business Innovation Research (SBIR) Phase II project addresses the technical challenge of predicting structural performance of an "as manufactured" fiber-reinforced 3D printed part. Additive Manufacturing (AM) offers the product engineer or designer tremendous freedom to create parts not achievable by more traditional processes. However, parts produced by AM are fundamentally different than those produced by conventional methods. For example, a machined aluminum part is largely homogenous, while a 3D printed part allows for internal lattice (infill) structures. A 3D printed part can also exhibit a multitude of process anomalies such as voids, delamination between layers, warping produced by residual stresses as the part cools, and, in the case of fiber filled plastics, fiber orientation that varies throughout the part. Collectively, these features can have a dramatic impact on the ultimate performance of the part and must be understood by the engineer early in the design stage. This project seeks to develop a commercial software simulation product that predicts the structural performance of a part produced by 3D printing, while optimizing the infill (lattice) structure for strength and weight. Speed, simplicity, and high-fidelity results are hallmarks of the proposed solution and are at the core of the value proposition.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TEXAS AT SAN ANTONIO, THEUniversity of Texas at San AntonioShouhuai Xu(210) 458-5739shxu@cs.utsa.edu09/21/2018$499,997$499,99710/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSaTC: CORE: Small: Collaborative: A Framework for Enhancing the Resilience of Cyber Attack Classification and Clustering Mechanisms1814825800189185042000273Secure &Trustworthy CyberspaceIndrajit Ray(703) 292-8950iray@nsf.govOne UTSA CircleSan AntonioTX78249-1644San AntonioUS20University of Texas at San AntonioTX78249-1644San AntonioUS20Classification and clustering are two important classes of machine learning techniques that have been widely used for cyber defense purposes. However, these mechanisms can be defeated by intelligent evasion attacks, such as Adversarial Machine Learning. Currently, there are no effective countermeasures against these sophisticated attacks. The objective of the project is to investigate effective countermeasures to make classification and clustering mechanisms robust against intelligent evasion attacks. The scientific contributions of the project include advancing our understanding of the feasibility and impact of evasion attacks, and the design of machine learning algorithms that are robust against such attacks. Since machine learning techniques are widely employed in many other areas such as real-world fraud and crime detection, those areas would benefit from this project too. The project will involve PhD students who will directly contribute to the next-generation workforce and will address diversity by involving female students and students from underrepresented groups.
The project plans to achieve its goal by investigating a more powerful class of attacks, called gray-box attacks, than the traditional black-box attacks investigated in the literature. In the gray-box attack model, the attacker can perform all the activities that a defender would normally perform. The project will build a theoretical model and framework for characterizing the vulnerability and resilience of classification and clustering mechanisms with respect to intelligent evasion attacks under the gray-box model, enhance classification and clustering mechanisms to withstand intelligent evasion attacks with quantifiable resilience gains.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CENTRAL FLORIDA BOARD OF TRUSTEES, THEUniversity of Central FloridaRoger Azevedo(919) 302-1867roger.azevedo@ucf.edu09/21/2018$12,515$12,51508/01/201808/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITConvergence HTF: Collaborative: Workshop on Convergence Research about Multimodal Human Learning Data during Human Machine Interactions1854175150805653159621697FW-HTF: Advancing Cognitive anJordan Berg(703) 292-8360jberg@nsf.gov4000 CNTRL FLORIDA BLVDORLANDOFL32816-8005OrlandoUS07University of Central FloridaFL32816-8005OrlandoUS07Intelligent, interactive, and highly networked machines -- with which people increasingly share their autonomy and agency -- are a growing part of the landscape, particularly in regard to work. As automation today moves from the factory floor to knowledge and service occupations, insight and action are needed to reap the benefits in increased productivity and increased job opportunities, and to mitigate social costs. Such innovations also have significant implications and potential value for lifelong learning, skills assessments, and job training/retraining in an environment in which workforce demands are changing rapidly. The workshop supported by this award will promote the convergence of cognitive psychology, learning sciences, data science, computer science, and engineering disciplines to define key challenges and research imperatives of the nexus of humans, technology, and work with focus on human affect, motivation, metacognition, and cognition during learning and problem solving. Convergence is the deep integration of knowledge, theories, methods, and data from multiple fields to form new and expanded frameworks for addressing scientific and societal challenges and opportunities. This convergence workshop addresses the future of work at the human-technology frontier.
The specific focus of this multi-phased workshop approach is to advance fundamental understanding of how to collect and analyze multimodal, multichannel sensor on human affect, motivation, metacognition, and cognition during learning and problem solving, and effectively integrate this data into actionable educational interventions in advanced learning technology environments (e.g., intelligent tutoring systems). The impacts of this research extend to a diverse range of learning environments, and job training and retraining opportunities. A multi-phased workshop approach will be used to explore the implications in multiple job sectors, and the outcomes will be broadly disseminated across geographic and disciplinary boundaries.VILLANOVA UNIVERSITY IN THE STATE OF PENNSYLVANIAVillanova UniversityBo Li(610) 519-6679bo.li@villanova.eduGanesh Balasubramanian, Jun Liu09/21/2018$15,050$15,05010/01/201803/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITTravel Support for Student Participation at the 2018 ASME-IMECE Micro and Nano Technology Forum; Pittsburgh, PA, November 12-15, 20181854005071618789071618789AM-Advanced ManufacturingKhershed Cooper(703) 292-7017khcooper@nsf.gov800 Lancaster AvenueVillanovaPA19085-1676VillanovaUS07Villanova UniversityDept Mech Eng, 800 Lancaster AveVillanovaPA19085-1676VillanovaUS07The purpose of this award is to provide partial travel support for 43 graduate and undergraduate students to attend the American Society of Mechanical Engineers International Mechanical Engineering Congress and Exposition in Pittsburgh, PA, from November 12-15, 2018. The students participate in a Society-Wide Micro and Nano Technology Forum (Topic 16-13), which focuses on new developments in the field of micro and nano engineering and science. The students present through oral and poster sessions their latest results to the broader Engineering community. Travel grants for the students are based on the technical quality of the poster abstracts submitted as well as on a statement from the students' research advisors. Priority is given to student participants who are women or who come from underrepresented groups, and to undergraduate students. This approach promotes diverse participation at the conference, in the short term, and in STEM fields, in the long term. This award benefits the nation through the education of a skilled and diverse engineering workforce better prepared to provide transformative solutions the challenges of their chosen fields.
This participation support is expected to benefit the students' professional, scientific and technical development. Attendance at the conference gives the students a broader view of the engineering profession and of state-of-the-art research in their fields via access to several technical and professional development talks by leading domestic and international speakers. Students enhance their communication skills through oral and poster presentations, in-depth discussions of their work with peers in their fields during the Society-wide Poster Symposium at the Micro and Nanotechnology Forum. This interactive experience significantly broadens student education, increases their enthusiasm for their research topic, acquaints them with expectations for scientific careers, and exposes them to new avenues for innovative research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MASSACHUSETTSUniversity of Massachusetts LowellAmy Peterson(508) 831-6029ampeterson@wpi.edu09/21/2018$274,099$274,09908/01/201805/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITGOALI: Experimental and Computational Approaches to Tailor Properties of Additively Manufactured Semi-Crystalline Polymers1853480956072490079520631Materials Eng. & ProcessingBrigid Mullany(703) 292-8360bmullany@nsf.gov600 Suffolk StreetLowellMA01854-3643LowellUS03University of Massachusetts LowellMA01854-3643LowellUS03Material extrusion, a form of polymer additive manufacturing in which a filament is extruded layer-by-layer onto a bed, can manufacture components with geometric complexity far beyond that possible with conventional manufacturing methods. Building the part in layers, which enables great geometric freedom, also limits the mechanical integrity of the printed part. The bonding quality between printed layers yields parts with lower mechanical strength than if they were manufactured by traditional molding methods. This Grant Opportunity for Academic Liaison with Industry (GOALI) research project seeks to understand how polymer properties and processing conditions interact, and how they can both be manipulated to enhance interlayer bonding in material extrusion additive manufacturing. The knowledge gained will be leveraged to both tailor polymer properties for additive manufacturing processes, and to print components with mechanical properties appropriate for functional applications. Success will greatly enhance the competitiveness of the US additive manufacturing base by providing a pathway towards the manufacture of cost effective, functional polymeric components. This award will also facilitate training of the future workforce; both graduate and undergraduate students will be involved in the research activities and will gain experience in advanced manufacturing and polymer science. As this is an industry-university collaborative project with Henkel Corporation, the students involved will also gain an understanding of industrial challenges and drivers. Planned workshops on polymer additive manufacturing will disseminate the knowledge to industries seeking new opportunities in this manufacturing arena.
This research will test the hypotheses that interlayer diffusion is a function of the difference between extrusion temperature and glass transition temperature, and that weld strength is dependent on the difference between the glass transition temperature and melt temperature as well as temperature-dependent wetting. This necessitates an understanding of the thermal characteristics of the material and the additive manufacturing process, and how they affect physical and mechanical properties of a printed structure. Towards this goal, three major research tasks will be undertaken: 1. Determine the role of the difference between the glass transition and melt temperatures in weld strength and residual stress of printed semi-crystalline polymers; 2. Understand the impact of crystallization kinetics on the crystalline morphology formed in additively manufactured structures; 3. Understand how glass reinforcement affects crystallization, heat transfer, and mechanical properties. By understanding the role of assembly conditions on resulting physical and mechanical properties, the work will lead to improved and tailorable physical and mechanical polymer properties essential to structure functionality. This research will also provide guidance in how to formulate polymers for additive manufacturing, based on thermal and physical properties.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CALIFORNIA, SANTA CRUZUniversity of California-Santa CruzJohn E Campbell(831) 854-7948elliott.campbell@ucsc.edu09/21/2018$1,240,734$1,240,73301/01/201808/31/2019GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCoastal SEES: Coastal fog-mediated interactions between climate change, upwelling, and coast redwood resilience: Projecting vulnerabilities and the human response1853039125084723071549000SEES CoastalBaris M. Uz(703) 292-4557bmuz@nsf.gov1156 High StreetSanta CruzCA95064-1077Santa CruzUS20University of California Santa Cruz1156 High StreetSanta CruzCA95064-1007Santa CruzUS20Coastal upwelling in eastern boundary currents drives some of the Earth's most productive and biodiverse marine ecosystems. While the contributions of upwelling to marine ecosystems are well-recognized, critical implications of upwelling for coastal terrestrial ecosystems are not. The main hypothesis of this study is that ocean-atmosphere-land interactions, mediated by coastal fog, cause upwelling to drive one of the Earth's most productive terrestrial ecosystems, coast redwood forests. The study further hypothesizes that learning about climate change impacts to this iconic species can influence perceptions of climate change. The future resilience of coast redwoods is now of critical concern due to the detection of a decline in coastal fog that may be associated with anthropogenic climate change and expanding urban heat islands. However, this coastal ocean-atmosphere-land system has received relatively little attention. This is largely due to the fact that until recently, earth system models were not capable of simulating the coastal fog that links the component systems, making it difficult to interpret historical observations or to project climate change impacts on these integrated systems. Furthermore, fundamental ecological measurements are obscured by the presence of fog, making it very difficult to understand how coast redwoods will respond to changes in fog. Understanding this coastal ocean-atmosphere-land system will not only provide much needed information for coast redwood resilience, but will also establish a foundation for future work on critical fog-mediated vulnerabilities to a range of coastal terrestrial, riparian, and intertidal ecosystems, and human-affected sectors including irrigated agriculture, wildfire management, public health, air and ground traffic, tourism, and urban energy and water consumption.
In this project, an interdisciplinary team will leverage recent advances in regional ocean-atmosphere-land modeling and laser spectrometry to provide an unprecedented exploration of this coastal integrated natural-human system. Activities to broaden the impacts of the project include outreach to land managers and interpreters, interactions between modeling and public outreach, participation in a climate change documentary, media outreach, and interdisciplinary training of Hispanic Serving Institution undergraduates and two postdoctoral scholars.
The results of this project will be (1) a process-level understanding of the coastal fog-mediated interactions between ocean-atmosphere circulation and coast redwood ecophysiology, (2) projections of fog, coast redwood resilience, and upwelling under anthropogenic scenarios of global greenhouse gas forcing and local urban heat islands along with the ocean-atmosphere-land feedbacks to this forcing, and (3) an understanding of how the projected vulnerabilities of this iconic coastal species can influence human perceptions about climate change and climate-friendly behaviors. The project will focus on three activities with essential linkages across the team: (1) U.S. Pacific Coast simulations of ocean and atmospheric circulation will be used to understand how the timing and strength of upwelling interacts with the atmosphere and coastal land systems to produce and maintain coastal fog (Samelson, Skyllingstad, de Szoeke, Oregon State Univ.; O'Brien, Lawrence Berkeley National Laboratory). (2) Laser spectrometer measurements of atmospheric carbonyl sulfide in coast redwood forests will provide the unique capability of measuring primary productivity and physiological regulation in the presence of fog (Campbell, UC Merced; Berry, Carnegie Institution; Dawson, UC Berkeley; Seibt, UCLA). The resulting ecological information will be used to develop regional simulations of coast redwood physiology under current and projected fog regimes. (3) The new scientific understanding of coast redwood resilience will form the foundation of surveys measuring human attitudes, knowledge, values, place connections, and current climate-related behaviors with regard to coast redwoods (Ardoin, Stanford Univ.). These survey data, along with the ecological data from ongoing research, will create a foundation for educational interventions that build on people's current place relationships, understandings, and existing behaviors.UNIVERSITY OF MARYLAND BALTIMORE COUNTYUniversity of Maryland Baltimore CountyRuey-Hung Chen(575) 646-1590chenrh@nmsu.edu09/21/2018$192,019$192,01908/01/201807/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITStudy of evaporation, micro-explosion, and combustion of nanofluid fuel droplets1852046061364808003256088Combustion & Fire SystemsSong-Charng Kong(703) 292-8695skong@nsf.gov1000 Hilltop CircleBaltimoreMD21250-0002BaltimoreUS07University of Maryland Baltimore CountyMD21250-0002BaltimoreUS07Many industrial applications involve evaporating liquid containing small-size particles. One example is to manufacture pharmaceutical powder aggregates in a way that they would be easily inhaled or ingested. In this application, the shape and density of aggregates determine the easiness with which the patient take the medication. Burning fuels containing particles, such as heavy fuel oils or rocket propellants, also involves similar evaporation process. In the case of burning fuels, the shape and density of the particle aggregates also affect the means and effectiveness with which particles are captured to minimize pollutant emissions. In this project, effects of particle size and concentration on liquid evaporation and burning will be characterized. The effort will be mainly experimental, aided by theoretical analysis for a full understanding of the evaporation, burning, and aggregate formation mechanisms. Both undergraduate and graduate students with diverse backgrounds will be recruited and involved in this project.
The proposed study uses the combination of the electrospray technique to generate fuel droplets containing nano-size energetic particles, which are freely suspended in space by the electro-dynamic balance. The droplet will then be ignited for combustion study, and the results will be compared with those without adding nano particles. The proposed study will answer the following specific questions: (1) Does the droplet burning follow the conventional d-square law due to the presence of particles and why? (2) Can the existing theory explain the non-d-square behavior? (3) How does the droplet burn when the droplet is electrically charged? (4) Is there secondary atomization during the single-droplet evaporation due to the Rayleigh charge limit (the critical charge density of a droplet)? (5) How does the aluminum particle affect the secondary atomization, Rayleigh limit, ignition, and burning? The proposed study is of great significance in advancing the power density of energy systems. This work has the main application in propulsion as adding metal energetic particles to liquid propellants can increase both the gravimetric and volumetric energy density of the propellant, thus increasing the range of the atmospheric flights and space vehicles. In addition to combustion, this work is also relevant to the dynamics of functional droplets, sprays, and heat/mass transfer. The results also have implications for other applications, such as food, pharmaceutical, ceramic, chemical, and nanotechnology.UNIVERSITY OF CALIFORNIA, DAVISUniversity of California-DavisMichele Barbato(858) 349-0054mbarbato@ucdavis.edu09/21/2018$9,940$12,19608/14/201808/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Engineered Earth Masonry for Affordable Seismic Resistant Low-Rise Buildings1850777047120084071549000Engineering for Natural HazardJoy Pauschke(703) 292-7024jpauschk@nsf.govOR/Sponsored ProgramsDavisCA95618-6134DavisUS03University of California-DavisDavisCA95618-6134DavisUS03There is a continuing demand in the United States for sustainable and hazard-resilient but highly affordable low-rise buildings for households and businesses. The goal of this research project is to investigate the feasibility of high-quality reinforced earth masonry (REM) for seismic resistant low-rise buildings. This goal will be achieved by transforming sustainable and locally appropriate but brittle unfired earth masonry into a stronger and more ductile system by using non-biodegradable recycled plastic fibers combined with internal steel reinforcement. This research will investigate REM as a low-cost option for low-rise industrial buildings and sheds, with a vision of fostering the development of small plants and warehouses by reducing construction and maintenance costs, thus promoting economic development.
The technical objectives of this research are the following: (1) to engineer, prototype, and verify an affordable and high-quality REM system for seismic resistant low-rise buildings, and (2) to formulate, verify and implement a new numerical model to accurately and efficiently predict the structural response of REM walls. The hypotheses are:v(1) engineering of earth blocks and mortar stabilized with nine percent or less cement, and reinforced with one percent or less volume fraction of recycled plastic fibers, combined with internal steel reinforcement, will change the strength and ductility of REM, making it suitable for seismic resistant buildings, and (2) computationally efficient numerical models based on newly developed nonlinear macroelements (MEs), whose kinematics are described by the smallest possible number of degrees of freedom, will enable the accurate prediction of the response of REM structures subject to static and dynamic loads. This research will be conducted in three phases. First, selected prototype block-mortar combinations (unreinforced, fiber reinforced, and fiber reinforced with grouted steel bars) will be characterized through load testing of materials and assemblages. A candidate reinforced system will be selected for the second phase. Three-dimensional (3D) digital image correlation (3D-DIC) will be used to measure full-field deformation maps and inform the development of numerical models. The resulting constitutive models for materials, mortar joints, and REM assemblages will serve to formulate detailed finite element (FE) models. Second, performance data will be obtained through large-scale testing and 3D-DIC monitoring of REM walls subject to quasi-static cyclic loading. The results will inform the formulation and validation of new structural ME models and their FE code implementation. Third and final, ME-based FE models of the large-scale specimens will be developed based on the comparison between numerical and experimental results. The resulting first-generation ME models will be used for a preliminary estimate of seismic design coefficients and factors to establish feasibility. In addition, a preliminary quantification of sustainability-related parameters and construction cost for representative REM materials and buildings will be performed to provide a basis for comparison with alternative systems, for example, light-framed wood, as well as life-cycle cost analysis.VANDERBILT UNIVERSITY, THEVanderbilt UniversityDaniel B Work(615) 322-2697dan.work@vanderbilt.edu09/21/2018$146,531$146,53103/19/201807/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCAREER: Modeling and Estimation Methods for Complex Traffic1853913965717143004413456CIVIL INFRASTRUCTURE SYSTEMSY. Grace Hsuan(703) 292-2241yhsuan@nsf.govSponsored Programs AdministratioNashvilleTN37235-0002NashvilleUS05Vanderbilt UniversityTN37235-0002NashvilleUS05The objective of this Faculty Early Career Development (CAREER) program award is to investigate the dynamics of complex traffic. Complex traffic is characterized by heterogeneous vehicle types (e.g. bikes and cars) that vary in size and performance characteristics but share the same infrastructure, and is often controlled by humans. These features are increasingly common in the US during extreme congestion generated by special events, and are pervasive in emerging economies worldwide. This research postulates that advances in mathematical models, informed by and validated with large volumes of traffic data, are key elements to unlock the full understanding of complex traffic. This research focuses on (i) the development of mathematical models of heterogeneous traffic, (ii) modeling and analysis of human-directed traffic and (iii) the development of fast and accurate estimation algorithms to integrate data into city-scale models. Data to validate the models and estimation algorithms are obtained through a newly developed traffic sensing technology.
If successful, this work will support the development of next generation traffic monitoring and management systems. Ultimately, this will help reduce the multibillion-dollar annual cost of congestion during special events in the US. Educational and outreach activities are executed to prepare students with the computing competencies needed to engineer the next generation of computer enhanced infrastructure. This is achieved through new educational initiatives for undergraduate and graduate students that emphasize programming and computational skills applied to problems in civil engineering. Reproducible computational research initiatives within the transportation community will help maximize the potential impact of the research and increase likelihood of adoption by practitioners. Engagement of the broader community on applications of computing in transportation is achieved through outreach and open courseware activities.RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIAUniversity of Virginia Main CampusNikolaos D Sidiropoulos(434) 924-6075nikos@virginia.edu09/21/2018$249,319$249,31909/01/201806/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRobust and Scalable Volume Minimization-based Matrix Factorization for Sensing and Clustering1852831065391526065391526COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govP.O. BOX 400195CHARLOTTESVILLEVA22904-4195CharlottesvilleUS05University of Virginia Main Campus351 McCormick RoadCharlottesvilleVA22904-4246CharlottesvilleUS05This project focuses on matrix factorization using a simplicial cone model, which has a wide variety of applications in remote sensing (particularly hyperspectral imaging), radio frequency sensing for dynamic spectrum access, clustering and topic modeling, and social network analysis, to name a few. The project focuses on robust and scalable computational tools for this model, using a convex hull volume minimization criterion. The motivation partially comes from a result that was recently obtained by the principal investigators, showing that unique factorization is possible under mild conditions if one adopts the volume minimization criterion. These conditions are far more realistic than those required by existing approaches, suggesting that more challenging scenarios and even new application domains are within reach if only related optimization, robustness, and scalability challenges can be effectively addressed. This research will provide the computational underpinnings of these exciting developments. High-performance volume minimization software will be publicly released to enable researchers and practitioners to tackle new problems, handle much larger datasets, and boost performance in existing applications like hyperspectral imaging. On the education front, the project will help train a graduate student in cutting-edge computational engineering research, and will also help engage talented undergraduates through senior honors projects, introducing them to research and publication opportunities.
In terms of theory and methods, key aspects of volume minimization-based matrix factorization are still poorly understood. The research will provide a set of high-performance computational tools rooted in deep understanding of the strengths and weaknesses of the original volume minimization criterion which promises exciting discoveries. The research will evolve along the following synergistic thrusts: i) robust optimization algorithms for volume minimization; ii) scalable and adaptive algorithms towards online volume minimization; iii) validation, using existing (e.g., hyperspectral imaging) as well as promising new (e.g., document clustering) applications; and iv) theoretical aspects of the volume minimization formulation, focusing on fundamentals such as identifiability and performance bounds. Devising scalable volume minimization algorithms makes a lot of sense for modern sensing and clustering problems which involve rapidly increasing amounts of data. From an applications point of view, volume minimization for spectrum sensing, channel identification, and document clustering are completely new and challenging.UNIVERSITY OF ARIZONAUniversity of ArizonaJonathan D Ellis(520) 621-4929jdellis@optics.arizona.edu09/21/2018$465,825$465,82409/30/201702/28/2022GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCAREER: Breaking the Freeform Optics Metrology Barrier with Synthetic Wavelength Interferometry1851739806345617072459266Manufacturing Machines & EquipSteven R. Schmid(703) 292-8611sschmid@nsf.gov888 N Euclid AveTucsonAZ85719-4824TucsonUS03University of ArizonaAZ85721-0158TucsonUS03Freeform optics use complex surfaces that are not necessarily axisymmetric, potentially very complex, and have many applications. A continuing problem is the measurement (metrology) of such surfaces. Existing metrology solutions use interferometry, but suffer from fringe visibility issues and other errors, while touch systems such as coordinate measuring machines and profilometry have insufficient accuracy (i.e., micrometer scale as opposed to nanometer scale) and may damage the optical surface, especially for softer materials. The PI will execute a multi-faceted research program aimed at improving the metrology of freeform optics. Central to his approach is the combination of two light sources, each with a different wavelength, in order to evaluate the surface profile of the lens. This approach will lead to the measurement of high aspect ratio surfaces, where interference fringes would normally be spaced too close together to discern from each other. This is enhanced by the consideration of trace and retrace (going over the same path in opposite directions with the light source), and the differences between the two measurements. The approach uses mathematical models that will be used to extract the desired geometry. The result is a methodology that can be used in measuring free-form optics to a higher resolution than currently possible. One Broad Impact of this Faculty Early Career Development (CAREER) program research project is to empower optical designers and manufacturers with metrology methodologies that can measure advanced freeform optics. Freeform optics are the foundation for future vision-based technologies and lightweight, portable, unobtrusive mobile devices. Potential devices range from compact satellites for monitoring environmental changes to better optical sensors for autonomous vehicles. This research will have educational impact at the university level through mentoring research assistants, incorporating research in undergraduate student experiential learning, and outreach with high school students. The PI performs outreach via high school outreach, through workshops, and through extensive podcasting and blogging activities.
This research will address this fundamental research question: Can synthetic wavelength interferometry (SWI) be used to produce new enabling capabilities in measuring freeform optics? The PI will examine (theoretically and experimentally) the impact of transmission sphere f-number and local slope departure on vignetting, in order to measure optics that normally have fringe ambiguity and retrace errors. This will be also investigated through the application of synthetic wavelength interferometry (SWI), where two light wavelengths are combined so that the phase difference can be examined and the limits to conventional interferometry can be identified and improved upon. The critical aspect of this technique is that the synthetic wavelength can be generated to resolve fringe ambiguities for lengths potentially much larger than the constitutive wavelengths. This is especially important for optics where the local slope departure is high. Fringe ambiguities arise from insufficient sampling of dense fringe patterns in interferometers, which create aliasing in the measurement. These ambiguities manifest from exceeding Nyquist sampling limits from high slope departure optical surfaces like steep aspheric and freeform optics. The investigations in this research will focus on two main aspects: dispersion effects from using synthetic wavelengths and retrace errors from steep slopes causing the returning light to pass through a different spatial location in the optical system. Both Fizeau and Twyman-Green interferometer configurations will be considered, as each system has a different placement of the reference surface and may cause different effects for both dispersion and retrace errors. The wavelength selection for the synthetic wavelength influences in both the non-ambiguity range and extending the Nyquist sampling limit. This, and the coupling with signal processing present potential contrasting criteria for utilizing synthetic wavelength interferometry for measuring freeform optics.UNIVERSITY OF GEORGIA RESEARCH FOUNDATION, INC.University of Georgia Research Foundation IncJin Ye(650) 867-5220jin.ye@uga.edu09/20/2018$360,000$360,00007/01/201807/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITLow-Torque-Ripple Sensorless Control of Mutually Coupled Switched Reluctance Machines (MCSRMs)1851875004315578ENERGY,POWER,ADAPTIVE SYSRadhakisan S. Baheti(703) 292-8339rbaheti@nsf.gov310 East Campus RdATHENSGA30602-1589AthensUS10University of Georgia Research Foundation IncGA30601-1077AthensUS09The proposed research will advance motor drive technologies by designing a novel control scheme for mutually coupled switched reluctance machines. Such machines are of great importance to satisfy the increasing demand for cost-effective, highly reliable and efficient motor drive systems in electrified transportation, industrial applications, and home appliances. Although induction and permanent magnet synchronous machines are currently dominating the market, due to the soaring prices and rapid depletion of rare-earth materials, researchers in the U.S. and world-wide are searching for rare-earth-free alternatives. Switched reluctance machines belong to the group of such alternatives. They are increasing in popularity due to their simple and rigid structure, fault-tolerant capability, and extended-speed constant-power range. However, conventional switched reluctance machines suffer from high torque ripples, acoustic noise, vibration, and non-standard asymmetric bridge power converters. Mutually coupled switched reluctance machines that are the focus of the proposed research are outperforming conventional switched reluctance machines as they can be driven by a standard six-switch converter. The proposed research will address these technical challenges impeding the widespread utilization of mutually coupled switched reluctance machines. The work will greatly advance the research in power electronics and motor drive technology and will promote research, teaching, training, and learning. The research will be integrated into the undergraduate and graduate electric power engineering curriculum to educate future engineers who will have the skills and knowledge to meet the emerging needs of the industry.
The goal of the proposed research is to develop a novel control scheme for mutually coupled switched reluctance machines using a standard six-switch converter to minimize torque ripples and enable position sensorless control. Three specific objectives will be pursued: (1) Reduce torque ripples through the use of a two-stage current profiling scheme. (2) Attain position sensorless control. (3) Use a six-switch standard converter to develop a low-torque-ripple sensorless control. Accomplishing the objectives of the proposed research will develop mutually coupled switched reluctance machines into the next generation of rare-earth-free electric machines by overcoming key obstacles high torque ripples and non-sensorless control. To date, the modeling of mutually coupled switched reluctance machines has originated from conventional switched reluctance machines; however, due to the unique torque production mechanism, this modeling approach will complicate control system developments. This work will also investigate nonlinear models of mutually coupled switched reluctance machines and integrate nonlinear models into the design of the two-stage torque ripple reduction scheme and position sensorless control, thereby bridging the gap between the modeling and control in the field of mutually coupled switched reluctance machines. In addition, a six-switch standard converter will be used to replace the asymmetric bridge converter to increase cost effectiveness and improve its suitability in electrified transportation, industrial applications, and home appliances.UNIVERSITY OF SOUTH FLORIDAUniversity of South FloridaDavid S Simmons(330) 972-6675dsimmons@uakron.edu09/20/2018$147,694$147,69408/07/201807/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Mechanistic understanding and control of soft interfacial nanorheology from molecular simulations and nanoresolved experiments1854308069687242069687242PARTICULATE &MULTIPHASE PROCESSusan Muller(703) 292-4543smuller@nsf.gov3702 Spectrum Blvd.TampaFL33612-9446TampaUS14University of South Florida4202 E. Fowler Ave. ENB 118TampaFL33620-5350TampaUS14CBET 1705738/1706012
PIs: Simmons, David S./Priestly, Rodney D.
From longer-lasting and safer batteries to strong and lightweight composites for use in airplanes and automobile bodies, many of the materials that could open the door to tomorrow's technologies incorporate structure on the nanometer scale. These materials are not composed of single uniform substance. Instead, these "nanostructured" materials consist of vast numbers of distinct alternating domains, each a thousand times smaller than the thickness of a human hair. With the proper design, these composites have the potential to combine the best properties of multiple materials into one. However, researchers have found the performance of nanostructured materials depends not only on the composition of the nanoscale domains, but also on the interfaces between the domains. The behavior of these interfaces, which are too small to characterize directly with current tools, remains unknown. This collaborative award will support experiments and computer simulations of molecular motion that will focus on these interfaces to understand the origins of their unique properties. The project will determine how these interfaces deform differently than the surrounding materials and how the interfacial deformation can be designed to yield materials with improved performance. The research team will engage high school and undergraduate students in an integrated research experience spanning the University of Akron and Princeton University, accelerating the understanding and discovery of new materials while broadening the U.S. technology workforce.
This project aims to 1) establish a mechanistic understanding of gradients in nanoscale rheological properties at polymer/polymer interfaces and their connection to molecular structure, and 2) pioneer a new strategy for the rational control of rheology and mechanics near polymer/polymer interfaces via the introduction of nanoparticle surfactants. A central challenge in accomplishing these goals has been a longstanding inability to resolve directly nanoscale gradients in rheological response near soft interfaces. This research will overcome this challenge via a feedback loop between high-throughput molecular dynamics simulations (Simmons) and experiments (Priestley). Experiments will combine layer-resolved fluorescence spectroscopy with a novel non-contact shear rheology method that enables nanoscale resolution of gradients in rheological properties near polymer interfaces. Simulations will incorporate high-speed coarse-grained simulations and chemically-realistic all-atom simulations. By systematically probing a matrix of polymer and interfacial properties, simulations and experiments will interconnect interfacial thermodynamics, segmental dynamics, and rheological response near polymer/polymer interfaces. These results will be combined with a matrix of simulations and experiments probing the effect of nanoparticle surfactants on interfacial deformation to establish a new mechanism-based strategy for control of interfacial rheological response via the targeted introduction of nanoparticle surfactants. Ultimately, results from this work will accelerate design of materials with targeted interfacial properties and deformation, enabling new nanostructured polymers for applications ranging from next-generation batteries to separations membranes to lightweight structural materials. In addition to engagement of students over a range of levels in a cross-institution training program, the PI's will extend the impact of this research through joint organization of a symposium at a national meeting focused on bridging polymer and interfacial phenomena research communities.UNAVCO, INCUNAVCO, Inc.Meghan Miller(303) 381-7514Meghan@unavco.orgCharles M Meertens, Glen S Mattioli, Donna Charlevoix09/20/2018$5,755,217$714,41809/01/201808/31/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth Ssystem Dynamics: Geodetic Facility for the Advancement of Geoscience (GAGE) - OPP Scope1851163142357032GAGERussell C. Kelz(703) 292-4747rkelz@nsf.gov6350 Nautilus Dr.BoulderCO80301-5394BoulderUS02UNAVCO6350 Nautilus DriveBoulderCO80301-5394BoulderUS02UNAVCO will develop, operate, and maintain a distributed, multi-user Geodetic Facility for the Advancement of GEoscience (GAGE). Geodesy characterizes the Earth's time varying shape, orientation in space, mass distribution, and gravity field. It has revolutionized the geosciences, by measuring Earth changes with unprecedented spatial and temporal resolution. The GAGE facility employs expert professional staff, with guidance provided by the scientific community, to manage and operate a set of foundational geodetic capabilities that are essential for current research support, as well as frontier geodetic activities that will enable future research. The facility will promote advances in our understanding of continental deformation; tectonic plate boundary processes; the processes that drive earthquakes, volcanic eruptions and landslide hazards; continental water storage, atmospheric, ice sheet and glacier dynamics; and interactions among these components of the Earth system. The geodetic capabilities provided through the GAGE facility contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data products from GAGE will be used by federal agencies including the National Aeronautics and Space Administration, the United States Geological Survey and the National Oceanic and Atmospheric Administration, for missions including spacecraft positioning, satellite orbit, and timing corrections; earthquake, tsunami, and volcano early warning; weather forecasting; water resources; and environmental management. State departments of transportation will use GAGE data to help support traffic monitoring and control and increasingly GAGE data will support commercial sector positioning needs including for agriculture, construction and surveying, transportation (including air, rail, and maritime), mining and resource exploration, and fleet vehicle tracking.
The GAGE facility will manage and operate: 1) global and regional continuously operating Global Navigational Satellite Systems (GNSS) and complementary geodetic technology networks; 2) portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) geodetic instrumentation testing and support service; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs that foster the development of the next generation geosciences workforce, are designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences, and engage the public by highlighting advances in geophysical sciences and their societal relevance. Innovative and transformative research that will benefit from GAGE examines both the dynamics of individual processes and the nonlinear interactions within and among larger Earth systems. The study of active processes from geocenter motion to the studies of the lithosphere, cryosphere, hydrosphere, and atmosphere requires understanding of the coupling and feedbacks across a range of length and time scales, and between the solid Earth and its fluid envelopes, in both physical and biological environments. Under NSF, and NASA partner agency support for GAGE, UNAVCO will integrate and federate a set of currently operated but at present independently managed GNSS stations to form the Network of the Americas (NOTA). UNAVCO will modernize NOTA stations with state-of-the-art, multi-sensor, multi-GNSS, receivers with real-time streaming data and analysis. These enhancements will enable higher precision positioning than currently possible and new application of GNSS data that can be used for geohazards warning systems, study of ocean and atmosphere dynamical behavior, and observation of key environmental parameters such as water storage, soil moisture, and sea and lake-level changes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TEXAS AT ARLINGTONUniversity of Texas at ArlingtonFrank L Lewis(817) 272-5972lewis@uta.eduAli Davoudi, Yan Wan09/20/2018$220,010$220,01009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Collaborative Research: Unified Theory of Model-based and Data-driven Real-time Optimization and Control for Uncertain Networked Systems1839804064234610042000273ENERGY,POWER,ADAPTIVE SYSAnthony Kuh(703) 292-2210akuh@nsf.gov701 S Nedderman Dr, Box 19145ArlingtonTX76019-0145ArlingtonUS06University of Texas at ArlingtonTX76019-0145ArlingtonUS06The project seeks to find a common decision-making framework that seamlessly integrates offline data and computing, real-time data and computing, learning, and probabilistic predictive decision. It provides a unified theory of model-based and data-driven real-time optimization and control for uncertain networked systems. Integral Reinforcement Learning holds the key to integrating real-time data-driven methods, model-based methods, and physical constraints. The structure of Integral Reinforcement Learning will be explored to investigate exactly how and where to use Deep Learning neural networks in architectures that have multiple nested learning loops. A probabilistic spatiotemporal scenario data-driven framework will then be developed for multi-scale sequential control of networked engineering systems under uncertainty. The algorithms and tools developed will be used to sculpt optimal power profiles for power electronics converters in a DC distribution network and help mitigate the adverse effects of intermittent sources, uncertain load demand, or faults.
The project represents a radical departure from the exiting big data and decision-making research, toward developing autonomous decision-making under uncertainty constructs for systems of growing scales and time critical mission requirements. Algorithms and tools developed can be extended to other smart and connected domains, e.g., air traffic management, networked traffic platoons, and sensor networks. US microgrid capacity is expected to reach 4.3 GW by 2020. DC distribution networks are emerging alternatives to AC distribution ones, and are critical to the scalable integration of renewable energy resources and electrified transportation fleets. Research results will be ported into topics in reinforcement learning, optimal control, networked control systems, data-driven analysis and decision-making, and power electronics systems. This project synergizes research activities between University of Texas at Arlington (UTA) and Texas A&M-Corpus Christi (TAMUCC), both HBCU/MI Hispanic Serving Institutions, and involves students from Electrical Engineering and Computer Science backgrounds.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.EMBR LABS, INCembr labs inc.Matthew Smith(413) 218-0629matt@embrlabs.comHui Zhang09/20/2018$749,995$749,99509/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSTTR Phase II: Connected low-power wearable technology that provides personalized thermal comfort in offices1831178079938987STTR PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov288 Norfolk St, STE 4ACambridgeMA02139-1430CambridgeUS05CBE, UC Berkeley390 Wurster Hall #1839BerkeleyCA94720-1839BerkeleyUS13The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to make significant contributions to the future of thermal environmental conditioning in buildings throughout the world. The connected, low power, wearable personal comfort systems can provide relief for the thermally-underserved of America's workforce (who are disproportionately female or part of the aging population), thereby improving their workplace wellbeing, satisfaction, and productivity. The personal comfort system could increase worker productivity by 2-3%, unlocking $17B economic output that is currently lost due to thermal discomfort in the United States, and could reduce the cost of space heating/cooling buildings by 20-30% when integrated into smart building systems. As roughly 10% of the world's energy is spent heating and cooling the interiors of commercial buildings, this technology can make an impactful contribution to the preservation of our planet and the wellbeing of future generations.
The proposed project will support the development and demonstration of a connected, low-power wearable personal comfort system that provides personalized thermal comfort to building occupants. Americans spend over 90% of their time indoors, buildings are responsible for about 40% of our total energy consumption, and yet over 40% of people in office buildings are dissatisfied with their thermal environments. The proposed project has the potential to correct this imbalance, improving occupant comfort and productivity while reducing the energy consumed by buildings. In Phase I, we demonstrated a connected, wearable personal comfort system that can improve the perceived environmental temperature by over +/-6 degF using only 1-2 W of power. In order to harness this enormous technological potential, this Phase II R&D will address remaining technical challenges around ergonomics and thermal management, intensively validate the efficacy of the devices in a laboratory setting, and culminate in deploying this technology in smart buildings and quantifying the effect on both the building and the building occupants.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.JOHNS HOPKINS UNIVERSITY, THEJohns Hopkins UniversityRui Ni(814) 308-3616rni2@jhu.edu09/20/2018$108,777$108,77709/12/201806/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITTurbulent multiphase flow with interfacial mass and heat transfer: linking microscopic physics to macroscopic mixing1854475001910777001910777PARTICULATE &MULTIPHASE PROCESSusan Muller(703) 292-4543smuller@nsf.gov1101 E 33rd StBaltimoreMD21218-2686BaltimoreUS07Johns Hopkins UniversityMD21218-2686BaltimoreUS07CBET - 1705246
PI: Ni, Rui
Many naturally occurring and industrial processes involve turbulent flows that contain particles such as bubbles or drops dispersed in a fluid. In these cases, the dispersed phase can exchange mass and heat with the surrounding fluid in a way that depends on details of the turbulent flow. This award will support experiments to understand the role of mass and heat transfer on large-scale statistics of turbulent flows. The challenge is to relate microscopic mass transfer on the scale of individual bubbles or drops to macroscopic mixing and mass transport. A vertical water tunnel will be used to study bubbles that can be held stationary and imaged to determine the concentration field of tracers that are exchanged between the bubbles and surrounding fluid. The rate of mass exchange will be correlated with parameters that describe the turbulence intensity and characteristics of the dispersed phase. An LED illumination system will be used to quantify temperature profiles in turbulent flow, which provides insight into large-scale mixing efficient of vapor bubbles. This system will also be used to study the concentrations of particles of various shapes to analyze mixing in turbulent flow. The results of these studies will be broadly relevant to such applications as evaporating sprays, rain droplets in clouds, air bubbles in fermentation reactors, and multiphase chemical reactors. The research team will prepare demonstrations of multiphase flows for K-12 student groups participating in programs at Penn State and for the Central Pennsylvania Festival of the Arts.
A vertical tunnel facility will be used to study mass transfer in particle-laden turbulent flows. An opposing mean flow balances the buoyancy drive rise or settling of particles, which allows the particles to remain in a field of view for imaging. The facility allows the mean flow and the turbulence Reynolds number to be adjusted independently. A combination of imaging methods will be used to measure the three-dimensional Lagrangian trajectories of dispersed particles, statistics of the surrounding flow, and the concentration field of mass exchanged between the two phases by interfacial transfer. Experiments will be conducted to identify the relevant parameters for turbulent multiphase flow with interfacial transfer. Flows containing bubbles and other particles with inertia will be examined to determine if inertial particles enhance mass transfer and mixing. The possibility of two-way couplings between interfacial momentum transfer and mass transfer will be investigated. The role of interfacial mass transfer on breakup and coalescence of bubbles will be determined.UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILLUniversity of North Carolina at Chapel HillMariana Olvera-Craviotomolvera@berkeley.edu09/20/2018$152,559$152,55907/01/201808/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITQueues in Cloud Computing1852282608195277142363428OE Operations EngineeringGeorgia-Ann Klutke(703) 292-8360gaklutke@nsf.gov104 AIRPORT DR STE 2200CHAPEL HILLNC27599-1350Chapel HillUS04University of North Carolina at Chapel Hill104 AIRPORT DR STE 2200CHAPEL HILLNC27599-1350Chapel HillUS04Cloud computing is a modern paradigm where computing tasks are performed on a subset of servers which coexist in a large distributed network of computers, called clouds. The number of computers in these clouds is rapidly increasing, surpassing hundreds of thousands today. Making large and parallel computing facilities generically available is desirable both from the business as well as the scientific perspective. Specifically, researchers today do not need to own an expensive supercomputer for studying complex systems, since they can tap into the cloud for hours, weeks or months at a time, well below the cost that they would need to pay to maintain a much smaller facility. This research will provide new tractable mathematical techniques for the analysis and efficient control of these large-scale systems.
The complexity of many of the systems used today for the distributed processing of large computing jobs makes it difficult to understand the impact of server information on designing scheduling protocols. The research done through this award will start by analyzing a mathematically tractable model for a network of servers where jobs are, upon arrival, split into a number of pieces, which are then assigned/queued at randomly chosen servers. The main characteristic of the model is that all pieces of a job must receive service in a synchronized fashion. This model, combined with a second model where jobs wait for the required number of servers to become available, will provide a benchmark for designing as well as quantifying the gains of practical scheduling policies. By noting that the two models constitute the extreme cases of having no server information versus having full, centralized information, this work will essentially provide a price for this knowledge, which will play an important role in designing future cloud systems.DUKE UNIVERSITYDuke UniversityVahid Tarokh(919) 660-7594vahid.tarokh@duke.edu09/20/2018$148,201$148,20106/01/201807/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Approximate Computing on Real World Data Using Representation and Coding1848810044387793044387793COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov2200 W. Main St, Suite 710DurhamNC27705-4010DurhamUS01Duke University140 Science DriveDurhamNC27708-9976DurhamUS01The diminishing benefits from traditional transistor scaling has coincided with an overwhelming increase in the rate of data generation. Expert analyses show that in 2011, the amount of generated data surpassed 1.8 zeta bytes and will increase by a factor of 50 until 2020. To overcome these challenges, both the semiconductor industry and the research community are exploring new avenues in computing. Two of the promising approaches are acceleration and approximation. Among accelerators, Graphic Processing Units provide significant compute capabilities. Graphic Processing Units, originally designed to accelerate graphics functions, now are processing large amounts of real-world data that are collected from sensors, radar, environment, financial markets, and medical devices. As Graphic Processing Units play a major role in accelerating many classes of applications, improving their performance and energy efficiency has become imperative. This project leverages the fact that many applications that benefit from Graphic Processing Units are amenable to imprecise computation. This characteristic provides an opportunity to devise approximation techniques that trade small losses in the output quality for significant gains in performance and energy efficiency. This project aims to exploit this opportunity and develop a comprehensive framework for approximation in Graphic Processing Units along with effective quality control mechanisms based on coding theory. Energy efficiency is arguably the biggest challenge of the computing industry. To maintain the nation's economic leadership in this industry, it is vital to develop solutions, such as this project, that address the fundamental challenges of energy-efficient computing. The computing industry has reached an era in which many of the innovative techniques, such as this work, crosses the boundary of multiple disciplines, including computer architecture, information theory, and signal processing. Thus, it is imperative to educate a workforce that not only deeply understands multiple disciples, but also can innovate across their boundaries. This project provides a foundation for such education and research. This project will produce benchmarks, tools and general infrastructure. These artifacts will be made publicly available and will be integrated in the Georgia Tech and Harvard curricula. To transfer these technologies, the principle investigators have established close contacts with several companies. Besides the customary routes academics use to disseminate results, the principle investigator will continue organizing workshops on approximate computing. The principle investigator is also coauthoring a book on approximate computing, which will include results from this project. The investigators are committed to diversity and inclusion of undergraduate, underrepresented, and high school students and are currently mentoring students from all groups that will continue throughout this project.
This project will first develop an accelerated architecture for Graphic Processing Units, which leverage an approximate algorithmic transformation for faster and more energy efficient execution. The core idea is to use neural models to learn how a region of code behaves and replace the region with a hardware accelerator that is tightly integrated within the many cores of the Graphic Processing Units. Second, inspired by Shannon's work and the success of random codes in providing reliable communication over noisy channels, this work will devise quality control solutions that utilize coding techniques to reduce the imprecision. The code is implicit in a sense that whenever an approximate output must be improved, its correlation with available exact outputs is exploited for constructing and decoding the code. Third, the project will study mechanisms that leverage the inherent similarity and predictability in the real-world data to address the memory bottlenecks in Graphic Processing Units. The main idea is to predict the values of a data load operation when it misses in the local on-chip cache and continue the computation without waiting for the long-latency response from the off-chip memory. To perform effective prediction, this project will develop multi-regime adaptive nonlinear time-varying dynamical models for the input data using our new theories of model matching.BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKAUniversity of Nebraska-LincolnDavid D Jones(402) 472-6716djones1@unl.eduSohrab Asgarpoor, Lance C Perez, Patricia Wonch Hill09/20/2018$199,999$199,99910/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITStatewide effort to diversify undergraduate engineering student population.1848696555456995068662618ENG DIVERSITY ACTIVITIESDana Denick(703) 292-8866ddenick@nsf.gov151 Prem S. Paul Research CenterLincolnNE68503-1435LincolnUS01University of Nebraska-LincolnNE68583-0861LincolnUS01This project seeks to investigate a framework that reassesses admissions criteria to deemphasize standardized tests by considering a holistic perspective of a student's academic experience. Research shows that putting too much weight on standardized tests results in a misrepresentation of a student's actual potential for academic success. Students, particularly students of color and women, are often negatively impacted by stereotype threat which has been shown to result in lower test scores. Therefore, test scores do not accurately reflect a student's ability.
To broaden participation in engineering, the College of Engineering at the University of Nebraska-Lincoln is broadening the admission review process to deemphasize standardized test scores and include a wider array of academic and social indicators. The changing demographics of Nebraska's high school graduates, and in particular the growth of the Hispanic/Latino/a population, make University of Nebraska-Lincoln an ideal place to study the impact of these changes on retention and graduation and the efficacy of subsequent student support programs for these students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TEXAS A&M UNIVERSITY-CORPUS CHRISTITexas A&M University Corpus ChristiJunfei Xie(361) 825-2177junfei.xie@tamucc.edu09/20/2018$79,963$79,96309/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Collaborative Research: Unified Theory of Model-based and Data-driven Real-time Optimization and Control for Uncertain Networked Systems1839707095100152042915991ENERGY,POWER,ADAPTIVE SYSAnthony Kuh(703) 292-2210akuh@nsf.gov6300 Ocean Drive, Unit 5844Corpus ChristiTX78412-5844Corpus ChristiUS27Texas A&M University Corpus Christi6300 Ocean DriveCorpus ChristiTX78412-5844Corpus ChristiUS27The project seeks to find a common decision-making framework that seamlessly integrates offline data and computing, real-time data and computing, learning, and probabilistic predictive decision. It provides a unified theory of model-based and data-driven real-time optimization and control for uncertain networked systems. Integral Reinforcement Learning holds the key to integrating real-time data-driven methods, model-based methods, and physical constraints. The structure of Integral Reinforcement Learning will be explored to investigate exactly how and where to use Deep Learning neural networks in architectures that have multiple nested learning loops. A probabilistic spatiotemporal scenario data-driven framework will then be developed for multi-scale sequential control of networked engineering systems under uncertainty. The algorithms and tools developed will be used to sculpt optimal power profiles for power electronics converters in a DC distribution network and help mitigate the adverse effects of intermittent sources, uncertain load demand, or faults.
The project represents a radical departure from the exiting big data and decision-making research, toward developing autonomous decision-making under uncertainty constructs for systems of growing scales and time critical mission requirements. Algorithms and tools developed can be extended to other smart and connected domains, e.g., air traffic management, networked traffic platoons, and sensor networks. US microgrid capacity is expected to reach 4.3 GW by 2020. DC distribution networks are emerging alternatives to AC distribution ones, and are critical to the scalable integration of renewable energy resources and electrified transportation fleets. Research results will be ported into topics in reinforcement learning, optimal control, networked control systems, data-driven analysis and decision-making, and power electronics systems. This project synergizes research activities between University of Texas at Arlington (UTA) and Texas A&M-Corpus Christi (TAMUCC), both HBCU/MI Hispanic Serving Institutions, and involves students from Electrical Engineering and Computer Science backgrounds.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIAUniversity of Virginia Main CampusHaiying (Helen) Shen(434) 924-8271hs6ms@virginia.eduCameron (Kamin) D Whitehouse, Benjamin A Converse09/20/2018$337,432$337,43209/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITPFI-RP: A Smart Building for Enhancing Human Performance, Comfort and Health1827674065391526065391526PARTNRSHIPS FOR INNOVATION-PFIJesus Soriano Molla(703) 292-7795jsoriano@nsf.govP.O. BOX 400195CHARLOTTESVILLEVA22904-4195CharlottesvilleUS05University of Virginia85 Engineer's WayCharlottesvilleVA22904-4740CharlottesvilleUS05The broader impact/commercial potential of this PFI project includes enhancing the workers' performance, comfort, health and well-being and saves billions of dollars for healthcare. This project will produce a new approach to integrating physical and human behavioral factors within a smart building system that has a high potential for commercialization. It will involve K-12, undergraduate and graduate students, and also will be used for new curriculum development. Female and under-represented students will be encouraged to participate in this project. The project will provide critical insight into creating human-centered smart buildings. Research results will be disseminated through publication, software and data release and technology transfer to industrial partners. The partnership with industrial partners will make the research deliverables have potential for commercialization. This project will create the foundation to launch a new inter-disciplinary research initiative in cyber-physical systems with potential for high impact on the nation's workforce.
The proposed project aims to build a human-centered context-aware responsive smart building that can provide personalized services to enhance the performance, comfort and health of occupants. The novelty of this project lies in its leveraging human behaviors in addition to the data from the physical world to provide context-aware automatic and personalized services that can better meet human needs. This smart building is unique by two features: 1) it provides personalized service rather than a universal service for all users; and 2) the building can automatically make context-aware adjustments to proactively meet user needs. This project consists of two innovations: 1) Social-based Context-aware Prediction/Response, and 2) Environmental Control for Human Health.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF SOUTH CAROLINAUniversity of South Carolina at ColumbiaMVS Chandrashekhar(803) 777-1118chandra@cec.sc.eduAsif Khan, Grigory Simin09/20/2018$370,890$370,89009/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITUltrawide bandgap AlGaN ionizing radiation detectors1810116041387846041387846ELECT, PHOTONICS, & MAG DEVICEDimitris Pavlidis(703) 292-2216dpavlidi@nsf.govSponsored Awards ManagementCOLUMBIASC29208-0001ColumbiaUS06University of South Carolina at Columbia300 Main StreetColumbiaSC29208-0001ColumbiaUS06Radiation detectors are critically important for environmental controls and monitoring of hazardous radioactive materials at airports and many others safety critical locations. Advanced nuclear detection is a timely issue for national security, nuclear power plants, and for military security. This project aims to develop highly sensitive, compact nuclear detectors using aluminum gallium nitride crystalline films produced using the same technology which was used for blue-green-white light emitting diodes and it was awarded the 2014 Nobel Prize. More recently an innovative extension of this technology using Aluminum Gallium Nitride materials has led to ultraviolet LEDs for air and water purification and power electronics for electric vehicles and advanced military radars. These developments offer low-cost and high sensitivity performance, with the potential of integrating functionalities such as lighting, ultraviolet detection, as well as radio transmission on a single microchip. This project proposes material and device innovations, to explore the use of Aluminum Gallium Nitride technology for low-cost, compact and highly sensitive nuclear radiation detectors. The challenge is the production of high quality material, which can withstand high temperatures and harsh environments, such as in a nuclear power plant. The team proposes to produce these materials and working electrical devices to benchmark against existing higher cost, bulkier legacy technology. The proposed work will lead to the education of at least 2 PhD students, 1 African American and 1 military veteran currently in the team's group, who will go into jobs in either government research or advanced manufacturing. The proposed research will further cement University of South Carolina?s track record of excellence in Aluminum Gallium Nitride materials for harsh environment electronics. During the PI's sabbatical at Morgan State University, a historically black university in Baltimore, MD, the devices produced in this work will be integrated into senior design projects.
The team proposes to develop a low-noise, high speed, ionizing radiation detector using ultra-wide bandgap aluminum gallium nitride epitaxial layers on aluminum nitride/sapphire templates. This ternary material is radiation hard and leads to devices with very low leakage currents even in harsh environments. It allows for monolithic integration with readout and power conditioning electronics, as well as other functionalities such as ultraviolet light sources. The proposed detector, a 2-5?m thick channel field effect phototransistor with a high internal current gain and low dark current will be grown by metalorganic chemical vapor deposition. It will be ideal for detecting pulses of radiation in Geiger mode, and eventually higher penetration radiation using thicker absorbing layers. The program exploits the shallow penetration deep ultraviolet light to improve materials development for thicker layers for soft beta radiation from Nickel-63. The ability to use monochromatic light enables characterization with spectral selectivity to the bandgaps, not possible with broadband beta-illumination. The team's initial experiments showed noise equivalent power <5fW, although these transistors had slow response times ~20s. Through a noise study, this was attributed to charge trapping at the aluminum nitride template/channel growth interface. The high current gain was partially a consequence of trapping induced photoconductivity. The growth solutions consist of electrically isolating this interface from the transistor channel, either with a thick strain engineered layer and/or a graded back barrier layer. Thus, any crystal growth strategy or device architecture that speeds up the device will lower photocurrent, but the Lorentzian noise arising from slow traps will also be reduced. Thus the tradeoff between current gain and speed, endemic to all detectors, is complicated by noise considerations, leading to the central question: How far can NEP and response time be decreased simultaneously by eliminating the influence of traps Initial analyses indicate that Nano-second to micro-second response times are possible, consistent with recombination times in direct gap semiconductors. The capability of engineering thick channel transistor layers directly translates to power electronics as well, as it enables the ability to block high voltages.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ARIZONA STATE UNIVERSITYArizona State UniversityJunliang Tao(216) 785-1376jtao25@asu.edu09/20/2018$500,000$500,00007/01/201806/30/2022GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCAREER: Integrated Research and Education on Bio-Inspired Burrowing1849674943360412806345658Geotechnical Engineering and MRichard J. Fragaszy(703) 292-7011rfragasz@nsf.govORSPATEMPEAZ85281-6011TempeUS09Arizona State UniversityAZ85287-7205TempeUS09This Faculty Early Career Development (CAREER) Program grant will promote the scientific understanding of the highly efficient burrowing mechanisms of animals in the natural world. Burrowing organisms can inhabit a wide range of subsurface soil types, and adopt a variety of burrowing strategies such as fracturing, digging, bulk fluidization, localized fluidization, localized grain rearrangement and compaction, facilitated by rhythmically changing their body shape. Several different species such as earthworms and bivalve mollusks possess extraordinary burrowing efficiency compared to most man-made penetrometers. Why the dynamic change in body shape is able to facilitate penetration in particulate soil is still largely unknown. From a geomechanical perspective, this award supports the discovery and fundamental understanding of the interaction between soil and bio-inspired penetrators with dynamic shapes. This research has potential to inspire the development of next-generation, high-efficiency underground construction technologies and versatile small-scale underground penetrometers. Application of these technologies can help reduce energy consumption and improve productivity; and underground sensing networks enabled by bio-inspired burrowing can help monitor the safety of infrastructure. Small, agile underground robots can also be used for normal geotechnical engineering site characterization, and also regions that are normally difficult to reach due to energy and environmental restrictions, such as the exploration of Mars or sites on Earth that are liquefied or damaged due to natural hazards (e.g., earthquakes, landslides, flooding, etc.). In addition, the new knowledge and techniques obtained through this research can be used to develop an understanding of the mechanical interactions between animal and sediment as well as shed light on the ecology and evolution of burrowing organisms. This research will serve as a platform to promote learning, teaching and training: the interdisciplinary and bio-inspired nature of the research is an ideal outreach topic to generate enthusiasm in K-12 students and the public about STEM education and research; the integration of the research approaches and findings into teaching and mentoring will help improve the image of geotechnical engineering and invoke students' interests in interdisciplinary research. The education objective of this project is to utilize this bio-inspired research to educate various audiences, including K-12 students, undergraduate and graduate students, and the general public, on biomimicry research for geotechnical engineering via two major pathways: (1) Partnering with GLBio, a dedicated organization in biomimicry innovation and education, the research outcomes will be disseminated to a broader audience including K-12 students and the general public. In collaboration with GLBio, a mobile interactive demo booth and an adaptable lecture module on the burrowing mechanism will be developed to educate the audience about biomimicry and interdisciplinary research. Outreach activities will be performed through GLBio's network, which includes schools, zoos, and museums in northeast Ohio. (2) A regional alliance for geotechnical engineering education in northeast Ohio (NEOGeo), involving public and private universities as well as local industry partners, will be established to integrate the educational resources and to improve their educational quality. To promote diversity and equality, priority will be given to qualified students from historically underrepresented groups (females and African-Americans), as well as students from low-income families and economically disadvantaged regions when recruiting students for the research program.
The research objective of project is to investigate the interaction between granular materials and bio-inspired penetrators with dynamic shape through integrated experimental and numerical models. The complexity of burrowing lies in the tempo-spatial change in the boundaries between granular materials and the burrower, as well as the solid-flow transition of the granular material. Experimental digital image correlation (DIC) techniques and the numerical discrete element method (DEM) are ideal for characterizing and modeling the granule dynamics, providing key multi-scale information to fully understand this dynamic structure-granule interaction problem. In this research, (1) a simple two-component apparatus utilizing an "artificial muscle" will be designed to mimic the burrowing kinematics of clams; penetration experiments with the artificial clam will provide ground truth multiscale observations of the soil-burrower interaction using DIC; (2) a virtual calibration chamber based on DEM will be developed and validated, and it will be used to investigate more fundamental mechanisms of burrowing at multiple length and time scales, as well as to systematically survey the effects of soil properties, soil stress states and burrower kinematics on burrowing performance. This research will ultimately answer the following questions: 1) Given a certain type of soil, how does the penetrator's changing shape affect the penetration efficiency? 2) Given the penetrator's dynamics and kinematics, how does the penetration efficiency (resistance) correlate to soil properties.CORNELL UNIVERSITY, INCCornell UniversityVladimir V Protasenko(574) 520-7726vvp7@cornell.edu09/20/2018$50,000$50,00010/01/201803/31/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITI-Corps: Deep Ultra Violet (DUV) - Light Emitting Diodes (LED) Disinfection: Commercialization of novel deep-UV light emitting diode module for disinfection applications1844808872612445002254837I-CorpsPamular Mccauley(703) 292-8950pamccaul@nsf.gov373 Pine Tree RoadIthacaNY14850-2820IthacaUS23Cornell University412 Phillips HallIthacaNY14850-2820IthacaUS23The broader impact/commercial potential of this I-Corps project will be to investigate the severity of the healthcare-acquired-infection (HAI) and related problems in US hospitals and to lay a foundation to solve the issues by employing panels of deep ultra-violet (DUV) light emitting diodes (LEDs) integrated with robotic platforms. Human beings are continuously attacked by viruses, bacteria, and microbes populating the air, water, and soil. It makes people sick and, in some cases, the illness becomes lethal. Special care needs to be taken for immunity deficient people in hospitals who are recovering from sickness or surgery. The 2011 report from Centers for Disease Control and Prevention states that approximately 722,000 patients in hospitals acquired additional infection and had to stay extra ~18 days for treatment. It resulted in additional $30 billion cost to US taxpayers. While it is relatively easy to disinfect floors, ceilings, desks, and other flat and even surfaces in hospital rooms by DUV light, there are hard-to-reach and shadowed areas that require special attention. Our team believes that advent of DUV LED integrated with remotely controlled robotic platforms can provide efficient disinfection of shadowed areas and thus reduce the number of HAI cases. We are in the midst of discussion of testing our robotic prototypes with the administration of the Health Division of Sault Tribe of Chippewa Indians tribe. It is a great opportunity for publicizing modern health care technologies among Native Americans. HAI is a global problem. In the past the United States was a leader in developing cutting edge technologies in medicine, telecommunication, defense, and aero-space industries. It is therefore vitally important for the US industry to keep producing new high-tech products. If an US team can show the path of controlling HAI it will definitely have a global impact.
This I-Corps project is based on the discoveries from an ongoing NSF-DMREF project. Our findings have shed light on how to overcome the major factors that limit the performance of DUV LEDs. In the research space a few unique properties of the PIs invented LEDs have been demonstrated: a) improved efficiency of light generation in ultra-thin GaN quantum wells, b) better light extraction efficiency, c) enhanced efficiency of carrier injection into quantum wells, and d) capability of LEDs to operate at cryogenic temperatures. Two provisional patent applications have been filed so far to protect the research outcome. Moving forward, our team has built a prototype by integrating commercial DUV LEDs with an autonomous robot to ensure human free disinfection of hospital rooms. It should be able to reach hard-to-access areas like space under beds and tables. We foresee that unique properties of our LEDs will reduce energy consumption by 5 times and enhance lifetime of LEDs. It will also lower the operating cost, improve disinfection of shadowed areas, and guarantee the absence of mercury, commonly found in mercury lamps, to ensure the absence of disposal problems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CASE WESTERN RESERVE UNIVERSITYCase Western Reserve UniversityDustin J Tyler(216) 368-0319dustin.tyler@case.eduChristian A Zorman, Mark Griswold, Suzanne M Rivera09/20/2018$100,000$100,00009/15/201808/31/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITPlanning Grant: Engineering Research Center for Human, Machine, and Network Functional, Symbiotic Integration On Neural Systems (Human Fusions)1840510077758407077758407ENGINEERING RESEARCH CENTERSDana Denick(703) 292-8866ddenick@nsf.govNord Hall, Suite 615CLEVELANDOH44106-4901ClevelandUS11Case Western Reserve University10900 EuclidClevelandOH44106-7015ClevelandUS11The Planning Grants for Engineering Research Centers competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.
This project will develop the foundational plan of an Engineering Research Center (ERC) to form a unique, transformative, and transdisciplinary team that will create, define, understand, and teach the science, technology, ethics, regulatory framework, entrepreneurship methodologies, and societal impact of the rapidly evolving integration of humans and technology. Communication and technology revolutions, such as radio, television, and the internet, have resulted in profound societal changes. The human, however, has basically remained external to the system with technology serving only as a tool. We propose that a conceptual shift toward symbiotic integration of the human with technology will bring the next societal transformation leading to a more connected, global society with new operational models of work, anthropocentric technology, and human-human interaction. We envision a tech-plus, transdisciplinary team of scholars, entrepreneurs, ethicists, and members from partnering institutions (including companies) that will perform convergent research at a new frontier of human incorporation of technology into a sense of self, i.e. a symbiosis between humans and technology. The core is a shift from the current techno-centric approach, where human and technology are separate, to a human-centric technology development paradigm. We seek to shift the societal dialogue from that of a battle between humans and technology (such as artificial intelligence and robotics) to a more productive dialogue of merging the best of humans and technology for the mutual benefit of both. Symbiotic incorporation of technology requires new interfaces to the human that add multiple sensory connections beyond current audio and visual inputs. This symbiotic relationship will augment human capability with those of technology and networked systems. New, symbiotic technology will radically change the future of work, human learning, human-human interaction, human networks, human health, human capability, and society overall for a safer, more prosperous future. The overall goal is to refine the model sufficiently to be compelling for a sustained research and development effort in an ERC for merging Humans, Machines, and Networks through Functional, Symbiotic, Integration On Neural Systems or an ERC for Human Fusions. Prior significant research shows that the core need of incorporation of technology into a human's sense of self, requires 1) a sense of agency over technology and 2) multi-sensory synchrony with technology.
Strictly, this project is a planning grant to develop the ERC structure and processes that will rationally evolve the relationship between humans and technology. Methods from the Science of Team Science (SciTS) will be employed to establish relationships between committed, energized stakeholders in this new, transdisciplinary effort in human-technology symbiosis and a strategic plan to grow and establish sustainable research capacity. The objectives of the project are to 1) assemble the expertise to define the transdisciplinary, tech-plus framework; 2) develop a process and the collaborative tools for the sustained, focused development and study of the new human-technology paradigm, and; 3) establish a central point of engagement for stakeholders and external communities. This project will foster a new dialogue regarding the evolution of the human-technology relationship. Tangible outcomes from the planning process will include social media networking platforms, a central collaboration and dissemination website, and surveys to gauge stakeholder commitment to and refinement of the symbiotic model of human-technology evolution. Successful realization of a symbiotic human-technology paradigm requires a transdisciplinary approach to address significant scientific, technical, ethical, and social challenges. The transdisciplinary model of the ERC for Human Fusions has a technical core addressing anthropocentric technology, multisensory human interfaces, and connection infrastructure. Expanding around this are disciplines to address ethical questions of symbiotic technology, regulatory frameworks to support the ethical principles, entrepreneurial models to introduce new technology, and sociology to understand how symbiotic technologies impact society. These are highly integrated such that each is integral to the development and understanding of the other. The potential ERC will provide leadership, intellectual resources, the establishment of world-class facilities for responsible and effective scientific discovery, technological innovation, and resources in the new symbiotic sciences for education, research and development and translation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.GEORGIA TECH RESEARCH CORPORATIONGeorgia Tech Research CorporationKyriakos G Vamvoudakis(540) 231-6707kyriakos@gatech.edu09/20/2018$499,339$88,78108/01/201804/30/2023GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCAREER: Towards an Intermittent Learning Framework for Smart and Efficient Cyber-Physical Autonomy1851588097394084097394084CYBER-PHYSICAL SYSTEMS (CPS)Jonathan Sprinkle(703) 292-8719jsprinkl@nsf.govOffice of Sponsored ProgramsAtlantaGA30332-0420AtlantaUS05Georgia Tech Research CorporationGA30332-0420AtlantaUS05This project expands how reinforcement learning frameworks can be used for Cyber-Physical Systems (CPS) for autonomy. The research utilizes intermittent reinforcement, where a reward is not given every time the desired response is performed. This differs from traditional reinforcement learning mechanisms, in which a reward is given for each point during online training. What is novel in this framework is that it can demonstrate how reinforcement learning can be used when rare events, or noisy and adversarial data, can affect the training and performance of these algorithms. The work will be validated on collaborative road freight transport and collaborative robotics testbeds, through international partnerships with Sweden and the United Kingdom. The project includes activities that integrate high-school students into challenging problems in machine learning areas, motivated through drone racing competitions.
The goal of this research is to expand foundational knowledge through deepened ties between the learning, control, game theory, and CPS communities. The approach is to, (i) unify new perspectives of learning in engineering with respect to resiliency, bandwidth efficiency, robustness, and other aspects that cannot be achieved with the state-of-the-art approaches; (ii) develop intermittent deep learning methods for CPS that can mitigate sensor attacks and can handle cases of limited sensing capabilities; (iii) incorporate nonequilibrium game-theoretic learning in CPS with components whose decision-making, rationality, and information usage are fundamentally different; and (iv) investigate ways to transfer learning to new platforms. The project's education and outreach component includes internships that will lead to technology transfer, summer camps with a special focus on reaching out to underrepresented minorities and women, and collaboration with institutions in Sweden and the United Kingdom through student exchange programs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MISSISSIPPI STATE UNIVERSITYMississippi State UniversityReuben F Burch(662) 325-7404burch@ise.msstate.edu09/20/2018$50,000$50,00010/01/201803/31/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITI-Corps, Humo Base: Ankle Complex Wearable for Kinematic and Kinetic Movement Data Capture and Assessment1844451075461814075461814I-CorpsPamular Mccauley(703) 292-8950pamccaul@nsf.govPO Box 6156MISSISSIPPI STATEMS39762-9662Mississippi StateUS03Mississippi State UniversityMS39762-6156Mississippi StateUS03The broader impact/commercial potential of this I-Corps project will be to improve the health and performance of sports, industrial, or military athletes on a court, in a warehouse, or serving our country, through a wearable liquid metal sensor solution. One of the largest over-use injuries that is prevalent in non-contact injuries, occurs at the foot and ankle, resulting in millions of dollars lost each year through missed time off and rehabilitation costs. Therefore, this wearable solution is designed to assess current movement patterns and function as a pre-rehabilitation device, which provides an assessment to warn wearers and practitioners of potential over-use movement patterns. In addition, the wearable can be used as a training device to ensure proper rehabilitation techniques and "back to work or play" range of motion assessments, ensuring effective decision making about when the wearer can and should return to activity. Based on wearable liquid metal technology, this device can be applied to all other joints in the human body, creating a wide range of uses which broaden our potential customer base beyond sports pre-rehabilitation of the ankle.
This I-Corps project takes the precision of research equipment out of the laboratory and into the environment where training actually occurs. The wearable device designed for this project is comprised of soft liquid metal sensors and a machine-learning computational platform that is both unrestrictive and non-obtrusive around the wearer's feet and ankles. Through pilot testing utilizing the gold standard of an optical motion capture system, specific sensor positions have been identified that provide linear relationships to the angular changes in single and tri-planar movement(s) of the ankle complex. Paired with wireless communication capabilities, the wearable device will allow managers, coaches, and other practitioners of human performance the opportunity to detect asymmetrical leg movement patterns that cause muscular imbalances and often lead to non-contact injuries. Through user experience (UX) testing protocols, software development will enable customizable user interfaces and reports that answers the "voice of the customer", looking for data from the ground up. Based on the results from laboratory testing, the next step is to field test the wearable device and synchronize data visualizations with appropriate mobile devices in order to gain deeper insight on customer wants and needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.OPTICAL SOCIETY OF AMERICA, INCORPORATED THEOptical Society of AmericaMichael Duncan(202) 416-1902mduncan@osa.org09/20/2018$10,000$10,00009/01/201802/28/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITIncubator Meeting on Metamaterial Films for In-Space Propulsion by Radiation Pressure, at OSA Headquarters, Washington, DC, 7-9 October 20181844332074825845ELECT, PHOTONICS, & MAG DEVICELawrence S. Goldberg(703) 292-8340lgoldber@nsf.gov2010 Massachusetts Avenue NWWashingtonDC20036-1012WashingtonUS00Optical Society of America2010 Massachusetts Ave NWWashingtonDC20036-1023WashingtonUS00Advanced photonic materials called metamaterials provide new opportunities to navigate space by means of radiation pressure. This Incubator meeting, to be held at The Optical Society headquarters on 7-9 October 2018, will support multiple coordination activities with academia and industry by bringing together experts in the areas of diffractive metamaterials, radiation pressure, and astronautics to advance the development of in-space sailcraft propulsion, navigation, and control. The goal of the program is to showcase promising new research and technology while building enthusiasm around and establishing a path toward solar or laser-driven sailcraft using passive or active films based on engineered transmissive or reflective metamaterials. By advancing the technology for new ways to maneuver in space, this Incubator will have broad impact on the economics of space utilization, affecting everything from communication and remote sensing satellites to solar system and interstellar probes. These advances will enhance partnerships between academia, industry, and NASA, improve national security, and increase the economic competitiveness of the US.
This Incubator meeting will bring together three different communities in space, materials, and opto-mechanics to stimulate and foster new applications for metamaterial films in light-driven space vehicles. As with many intellectually active areas in science, where advances come from the intersections between otherwise separate disciplines, the meeting will combine the relevant experts in the three communities to advance the understanding of how metamaterial films can be used to opto-mechanically steer sailcraft in outer space. Intellectually, the impact will be to stimulate advanced thinking of metamaterial film composition given the limitations of weight and thickness for space applications and to stimulate innovative uses of such a capability by spacecraft and satellite designers. The benefits will be to advance knowledge in how to create relevant materials and metamaterials for space sailcraft applications and to advance how spacecraft designers think about propulsion mechanisms with new capabilities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.LEHIGH UNIVERSITYLehigh UniversityYahong R Zheng(610) 758-5499yrz218@lehigh.edu09/19/2018$156,753$156,75308/31/201812/31/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: Synergy: Collaborative Research: DEUS: Distributed, Efficient, Ubiquitous and Secure Data Delivery Using Autonomous Underwater Vehicles1853257808264444068570936CYBER-PHYSICAL SYSTEMS (CPS)Sylvia J. Spengler(703) 292-8930sspengle@nsf.govAlumni Building 27BethlehemPA18015-3005BethlehemUS15Lehigh University400 Packard LaboratoryBethlehemPA18015-3005BethlehemUS15Ocean Big Data (OBD) is an emerging area of research that benefits ocean environmental monitoring, offshore exploration, disaster prevention, and military surveillance. It is now affordable for oil and gas companies, fishing industry, militaries, and marine researchers to deploy physical undersea sensor systems to obtain strategic advantages. However, these sensing activities are scattered, isolated, and often follow the traditional "deploy, wait, retrieve, and post-process" routine. Since transmitting information underwater remains difficult and unreliable, these sensors lack a cyber interconnection, which severely limits ocean cyber-physical systems. This project aims to providing a viable cyber interconnection scheme that enables distributed, efficient, ubiquitous, and secure (DEUS) data delivery from underwater sensors to the surface station. The proposed cyber interconnection scheme features cheap underwater sensor nodes with energy harvesting capability, a fleet of autonomous underwater vehicles (AUVs) for information ferrying, advanced magnetic-induction (MI) antenna design using ferrite material, distributed algorithms for efficient data collection via AUVs, and secure data delivery protocols. The success of this project will help push the frontier of Internet of Things in Oceans (IoTO) and OBD, both of which will find numerous underwater applications in offshore oil spill response, fisheries management, storm preparedness, etc., which impact the economy and well-being of not only coastal regions but also inland states. The project will also provide special interdisciplinary training opportunities for both graduate and undergraduate students, particularly women and minority students, through both research work and related courses on underwater wireless communication, network security, and AUV designs.
The DEUS project provides a viable cyber interconnection scheme that enables distributed, efficient, ubiquitous, and secure data delivery in underwater environment via four synergistic thrusts: (1) integration of underwater wireless sensor and communication systems, which will enhance the current MI and light communication means of underwater sensors, integrate acoustic transmission systems for long-range communications between anchor nodes and AUVs, and design energy harvesting and replenishment solutions to prolong the lifetime of underwater sensors (30+ years); (2) distributed and ubiquitous data delivery via multiple AUVs, which aims to collect the distributed data and deliver them ubiquitously throughout the underwater network by employing ferrite material and triaxial induction antennas and mounting them outside of the AUV body for MI enhancement, and developing algorithms of multiple AUVs' path-planning, trajectory optimization, etc. under dynamic network conditions; (3) efficiency and security in data delivery, which designs network algorithms to improve the efficiency and security of data delivery. Instead of collecting data from every sensor via acoustic communications, the AUVs choose some sensors to collect data with the high data rate transmission mode in near field (e.g., light), and allowing the sensor far away from the AUVs to send its data either directly to AUVs via acoustic wave or to its nearby chosen sensors via MI/light communications. A secure data delivery scheme will also be developed to not only secure the data delivery against typical malicious attacks and guarantee the integrity of collected data, but also allow the data aggregation of one business entity without knowing others' private business information; (4) experimental validation and testing, which will verify the proposed data delivery schemes, and quantitatively present the performance gains through simulations, experiments and field test, based on existing facilities.UNIVERSITY OF PUERTO RICOUniversity of Puerto Rico MayaguezFabio Andrade(787) 831-2065fabio.andrade@upr.eduEmmanuel Arzuaga, Agustin A Irizarry09/19/2018$355,640$355,64009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Development of a Real-world Microgrid Simulation/Testing Instrument1828443175303262090051616MAJOR RESEARCH INSTRUMENTATIONAnil Pahwa(703) 292-2285apahwa@nsf.govCall Box 9000MayaguezPR00680-9000MayaguezUS00University of Puerto Rico MayaguezMayaguezPR00680-9000MayaguezUS00Microgrids are a powerful means of increasing the use of Renewable-Energy-Sources (RES), an important part of the evolution of both Smart Grids and distribution systems. The proposed microgrid testbed is an experimental and educational platform for companies, communities and research institutions that are developing solutions for the integration of RES and intelligent appliances. The microgrid testbed promotes the progress of science and fosters prosperity and welfare by advancing the integration of RES into the existing electric-grid while increasing the reliability of the grid. It will improve the overall energy efficiency by reducing peak-capacity requirements using developed techniques like demand-side management and new tools such as smart plug-in-vehicles deployment. This contributes to advance the state-of-the-art in microgrid infrastructure research. Results can improve future designs and deployments of microgrids while supporting the NSF-mission to promote the progress of science.
The microgrid testbed integrates experimental research, development and education platforms in a single operational system. It is designed to run experiments at all levels of controls to conduct research on microgrids and smart grids, RES, energy storage, visualization of scenarios, cooperative control among distributed generators, and energy management systems. The facility is composed of a real-time simulator (RT-Lab) and an inverter-based setup, two electronic DC power-sources, loads, a 1kW PV-array on the rooftop of the building and two computers. The setup consists of four inverter-based-generators controlled by intelligent controllers and the RT-Lab to make them flexible enough to simulate DC and AC microgrids. One inverter-based-generator has a back-to-back configuration to emulate different kinds of energy sources and analyze the behavior in the DC-link. The system can also be connected to the public grid to test interactions between both. Further, the system will have capabilities to program some faults and test power quality problems. One of the key capabilities of the facility is the flexibility to change the software and firmware of each converter by using open firmware converters and intelligent control units. This provides a platform to attract researchers, government agencies and the community into microgrid-related activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.WAYNE STATE UNIVERSITYWayne State UniversityMark Ming-Cheng Cheng(313) 577-5462mcheng@wayne.eduCharles H Winter, Zhixian Zhou, Eranda Nikolla, Pai-Yen Chen09/19/2018$501,846$501,84610/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI:Acquisition of an UV-Vis and X-ray Photoelectron Spectroscopy (UPS/XPS) for Research and Education in Electronics and Advanced Materials1849578001962224001962224MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.gov5057 WoodwardDetroitMI48202-3622DetroitUS13Wayne State University5050 Anthony Wayne DriveDetroitMI48202-3622DetroitUS13The objective of this project is to advance research and education in the areas of electronics, sensors, nanomaterials, catalysis, and energy at Wayne State University (WSU) through the acquisition of a state-of-the-art ultraviolet and X-ray photoelectron spectroscopy (UPS/XPS) instrument. Particularly, the proposed UPS/XPS will be used as an enabling tool for several projects which urgently need the capability of the proposed instrument to characterize the physics and chemistry of material surfaces with high sensitivity and spatial resolution. UPS/XPS will significantly improve the quality and productivity of research at WSU in a broad range of areas. The acquisition of UPS/XPS will permit synergistic opportunities for device, material, biomedical, and energy research at WSU. It will also enhance the quality of research training of undergraduates and graduate students. Together, this proposed UPS/XPS instrument is expected to impact more than 100 users from 20 research groups. For local industry, it will serve as a resource for advanced battery manufacturing critical to the economic growth of southeastern Michigan. Students from underrepresented groups including minorities, women, and students with disabilities will be recruited using existing science, technology, engineering, and mathematics (STEM) programs at WSU.
UPS/XPS is a unique and invaluable tool to understand surface chemistry in material synthesis as well as physical and/or chemical treatments. It is an essential tool to study the work function and valence band of new materials and to quantify chemical elements and the bonding of atoms within the top 2 nm to 10 nm of the sample surface. The proposed instrument enables 4 unique capabilities, including (1) sensitive quantification in chemical measurements, (2) scanning XPS microprobe analysis, (3) UV Photoelectron Spectroscopy, and (4) micro area depth profiling. Therefore, the acquisition of UPS/XPS will significantly improve the quality and productivity of on-going research at WSU in a broad range of areas from the development of next-generation electronics (e.g., 2D materials beyond graphene, atomic layer deposition) to biomedical applications (e.g., biosensing, point-of-care devices) and to energy applications (e.g., catalysis, fuel cells, lithium ion batteries, green chemistry, and sustainability). Our long-term goals are to strengthen WSU research facilities in order to support research and education, to offer state-of-the-art characterization equipment to the scientific community of southeastern Michigan, and to enhance research and education/training of graduate, undergraduate, and high-school students in the greater Detroit area by offering hands-on learning experience.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ROOSEVELT UNIVERSITYRoosevelt UniversityMeng Yu(312) 341-2244myu04@roosevelt.edu09/19/2018$32,940$32,94009/01/201808/31/2019GrantNSF4900490047.076040106 NSF Education & Human ResourceEDU: Collaborative: Integrating Embedded Systems Security into Computer Engineering and Science Curricula1854494042531418042531418Secure &Trustworthy CyberspaceVictor P. Piotrowski(703) 292-5141vpiotrow@nsf.gov430 S Michigan AvenueChicagoIL60605-1394ChicagoUS07Roosevelt UniversityIL60605-1394ChicagoUS07With the advancement of technologies, networked devices become ubiquitous in the society. Such devices are not limited to traditional computers and smart phones, but are increasingly extended to cover a wide variety of embedded systems (ES), such as sensors monitoring bridges, electronics controlling the operation of automobiles and industrial equipment, home medicine devices that are constantly reporting patient health information to doctors. While the wide deployment of networked ES significantly benefits various aspects of human life and society at large, it also poses daunting security challenges that can put national security as well as the privacy of ordinary citizens at risk. Adequately addressing such challenges requires advanced technologies to be developed by industries and ES designers as well as users to be well educated about the security related issues. To facilitate technology development and better educate future designers, this project develops curricula focusing on the unique challenges of the emerging ES security, which has not been systemically covered in existing computer security related curricula that emphasize security in computers and the traditional Internet.
This project makes intellectual contributions through the completion of the following objectives: 1) developing course modules (lecture notes, labs and evaluation questionnaire) to introduce ES security in the layers of software, networking, operating system, architecture, and hardware; 2) integrating the developed material into several existing undergraduate courses at PIs' Universities; 3) establishing a unified ES security course with two versions (computer engineering and computer science versions) by integrating the developed course modules; 4) getting the developed material evaluated by an External Advisory/Review Committee; 5) teaching the developed material using both project-based learning and flipped classroom learning; 6) assessing the proposed teaching methods using formative and summative approaches; 7) broadly disseminating the developed material and promoting diversity in ES security education. Material to be developed will reach over 100 students per year, including many minorities and women.UNIVERSITY OF ILLINOISUniversity of Illinois at ChicagoCornelia Caragea(814) 308-4974cornelia@uic.edu09/19/2018$230,000$230,00008/27/201807/31/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-SUSTAIN: Collaborative Research: CiteSeerX: Toward Sustainable Support of Scholarly Big Data1853919098987217041544081COMPUTING RES INFRASTRUCTUREWendy Nilsen(703) 292-8930wnilsen@nsf.gov809 S. Marshfield AvenueCHICAGOIL60612-4305ChicagoUS07University of Illinois at ChicagoIL60612-4305ChicagoUS07Access to the scientific and scholarly literature has changed radically in recent decades. Increasingly researchers and scholars make their publications freely available on the Web. Taking advantage of this opportunity, new scientific search engine tools have been developed such as Google Scholar, Semantic Scholar, and CiteSeer, now CiteSeerX. CiteSeerX has become one of the most comprehensive and widely-used online public resources for the Computer and Information Science and Engineering (CISE) research community. Millions of CiteSeerX Portable Document Format (PDF) documents are indexed by Google. CiteSeerX is unique among digital library search engines. It is open access, most all of its documents are harvested from the public Web, and users have full-text access to all documents searchable on its website. Moreover, it provides all automatically extracted metadata and citation context via an Open Archive Initiative (OAI) metadata service interface and bulk downloads on a public cloud - all under a Creative Commons license. This service is usually not available from other scholarly search engines. CiteSeerX performs automatic extraction and indexing of tables (in production), figures (developed)}, and algorithms (developed), capabilities rarely seen in other scholarly search engines. CiteSeerX provides its open source software and architecture on GitHub. At this time none of the other above-mentioned systems release their digital library software.
Utilizing the established CiteSeerX infrastructure, this proposal aims to create a sustainable CiteSeerX system with new data resources and a much larger data collection. We will develop a new system that runs with low operation overhead, without a single point of failure, and that provides quality and enriched data and metadata in portable formats that will be available through accessible user interfaces. We will ingest all freely accessible scientific documents on the Web, currently estimated to be 30 million. CiteSeerX will make available high-quality metadata through an accessible Web User Interface, Application Programming Interface, and data dumps. SeerSuite, the platform on which CiteSeerX is built, will be refactored so as to be an easily deployable and configurable scholarly digital library framework. It will be built on commercial grade open source software. In addition, we will provide searchable semantic metadata, such as key phrases and disambiguated author names, and non-textual content such as data from figures, tables, algorithms, and equations. For long-term sustainability we will explore different monetization models. The result will be a refactored digital library search engine that provides stable, usable, and reliable data services on multiple types of scientific documents built on a portable, maintainable, and self-contained framework that can be deployed for other research document digital collections. Source code will be hosted at https://github.com/SeerLabs. System development and related research will be published in relevant venues and be made publicly available.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF BOSTON UNIVERSITYTrustees of Boston UniversityEnrico Bellotti(617) 358-1576bellotti@bu.edu09/19/2018$46,179$46,17910/01/201809/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITWorkshop on Electronics, Photonics and Magnetics (EPM) - Network for Computational Nanotechnology (NCN), To Be Held October 11-12, 2018, Alexandria,VA1851363049435266049435266COMMS, CIRCUITS & SENS SYSJenshan Lin(703) 292-7950jenlin@nsf.gov881 COMMONWEALTH AVEBOSTONMA02215-1300BostonUS07Trustees of Boston UniversityMA02215-1300BostonUS07The Workshop on Electronics, Photonics and Magnetics (EPM) - Network for Computational Nanotechnology (NCN) will be held on October 11-12 at the Holiday Inn, Alexandria, VA. It will allow to discuss issues related to development of computational tools to support the field of electronics, photonics and magnetics. The Workshop will host leading researchers in the field that will discuss the current state of the art, outline the pathways that allow efficient computation of nano/quantum devices, and propose, prioritize realistic research and development approaches that can lead to Computational Nanotechnology team efforts on Electronics, Photonics and Magnetics. There will be opportunities for information exchange and discussions on the development of computational tools to support the field as well as representing the community of users of these tools. Of major importance will be to determine possible ways a Node on Electronics, Photonics and Magnetics will allow efficient development of new tools and content dissemination worldwide via NSF's NCN Cyber Platform. Computation and simulation tools of this type will then be possible to be employed for turning nanoscale science and engineering into applications and impact future circuit and systems responding to grand challenges. There will be several plenary talks the will outline the state of the art in each area. Moreover, the plenary session will set the stage for the presentations and discussions in the breakout sessions that will be centered on the above mentioned four main themes. Each breakout session will feature several additional speakers that will focus on the details of specific topics related to the four different themes. A white paper will be prepared that outlines the current state of research, the opportunities and challenges, and the priority research and development directions. The Workshop is expected to play a key role in identifying new directions for research on novel electronic, photonic and magnetic devices for future systems. The white paper to be prepared will be made available to all interested parties and will allow better understanding of the modeling and computation field and its applications to a broader community.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PURDUE UNIVERSITYPurdue UniversitySaurabh Bagchi(765) 494-3362sbagchi@purdue.eduJitesh H Panchal, Milind Kulkarni, Gesualdo Scutari, Felix Xiaozhu Lin09/19/2018$49,500$49,50010/01/201809/30/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITNSF Workshop on State-of-the-Art and Challenges in Resilience1845192072051394072051394CYBER-PHYSICAL SYSTEMS (CPS)David Corman(703) 292-8950dcorman@nsf.govYoung HallWest LafayetteIN47907-2114West LafayetteUS04Purdue University465 Northwestern AvenueWest LafayetteIN47907-2035West LafayetteUS04Our society is crucially dependent on several interdependent critical infrastructure systems and processes for operating these systems, such as, industrial control systems, IoT systems underlying our smart cities, large-scale cyber systems, and built environments like transportation and building infrastructures. These are subjected to various kinds of hazards and faults, both natural and malicious, often leading to user-visible failures. The research community has developed a set of tools to analyze the failure modes of the infrastructures and systematically build in resilience. This workshop is meant to bring together select members of these communities who have focused on resilient and adaptive cyberinfrastructures, resilient cyber-physical systems, and scientific foundations of resilient socio-technical systems. The participants will be thought and action leaders in the area of social-technical resilient systems, drawn from external academic researchers and industrial practitioners. The workshop will stress the scientific and foundational research on resilience at the interface of multiple domains, and to promote applications of societal importance in these domains. This workshop will highlight the synergies through discussion of foundational techniques and case studies. Then it will present the salient research and practice challenges that can serve as a call-to-arms for the respective technical communities.
The workshop has three broad aims. First, to capture in one accessible forum best practices in research on resilience spanning multiple research communities. Second, to disseminate to the community what are the broad open research challenges, along with prior and ongoing work that can be leveraged to attack these challenges. Third, to provide artifacts (video lectures, design documents, software releases) documenting the progress the community has made in resilient system design and implementation. The workshop, to be held at Purdue University, will reflect on the current state-of-art and state-of-practice of resilient system design and will lay out the broad research and translation challenges that we will need to address to make our infrastructures truly resilient to natural failures. The workshop will be broad-based in the topical areas of cyber, cyber-physical, and socio-technical systems. It will draw from the technical contributions made by the communities, put them in the context of evolving technological changes, and identify broad-based topic areas where resilience work is both needed and likely to have high impact. The NSF communities that are natural fits within this workshop are: Smart and Connected Communities (S&CC), Cyber Physical Systems (CPS), Computer Systems Research (CSR), Software and Hardware Foundations (SHF), and Engineering Design and System Engineering (EDSE). We will invite researchers from these communities from various universities and at different levels of seniority to participate in the technical talks, panel discussions, and poster sessions. There will also be select industry and national lab participants. Three specific deliverables will come out of the workshop: reports (one for each topical area) documenting the current state-of-art, state-of-practice, and open research challenges in designing, developing, and maintaining resilient infrastructures; organized and curated material (slides, audio, video) of talks and panels; archive of posters presented by upcoming researchers on current research directions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RECTOR & VISITORS OF THE UNIVERSITY OF VIRGINIAUniversity of Virginia Main CampusOlivier R Pfister(434) 924-7956opfister@virginia.eduJoe C Campbell, Andreas M Beling, Xu Yi09/19/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: Quantum mux/demux: the quantum optical frequency comb as a scalable quantum encoding resource1842641065391526065391526COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govP.O. BOX 400195CHARLOTTESVILLEVA22904-4195CharlottesvilleUS05University of Virginia Main Campus382 McCormick RdCharlottesvilleVA22904-4714CharlottesvilleUS05RAISE-EQuIP:Quantum Mux/Demux: The Quantum Optical Frequency Comb as a Scalable Quantum Encoding Resource
Quantum information and quantum computing are emerging fields that have the potential to revolutionize various areas in science and technology. As first foreseen by Richard Feynman, quantum computers will enable calculations at currently unattainable scales and will bring unprecedented advances over classical computers. Examples include calculations of large biological molecules for revolutionary drug discovery, solving complex quantum mechanical systems, and factoring integers at a speed exponentially faster than classical computer to defeat current standard encryption methods. Quantum information is also fundamentally distinct from classical information. It cannot be cloned or hacked and therefore brings new power for cryptography, such as the method of quantum key distribution to create secure communications channels. The realization of practical systems capable of quantum computing and information is an extraordinary difficult task but will have profound impacts on national security and our society. To date, two primary challenges have been identified in making quantum technology a reality: achieving scalability and circumventing decoherence. At this juncture, many proof-of principle results have been experimentally demonstrated to address either decoherence (trapped-ion, superconducting, and cold atom qubits), or the scalability problem (field qumodes), but both requirements have not been met simultaneously yet. This project will address both of these challenges by a joint interdisciplinary effort between the Electrical and Computer Engineering and the Physics Departments at University of Virginia by ways of scalable integrated quantum photonics.
The aim of this project is to marry scalable integrated photonics with quantum information and quantum computation over continuous variables in order to encode quantum information over the quantum optical frequency comb (QOFC). Such technology will empower unconditional quantum protocols such as quantum communication, quantum entanglement distillation, and quantum simulation. With NSF support, the quantum optics group at the University of Virginia has been pioneering the implementation of QOFC in optical parametric oscillator and has achieved record-levels of multipartite entanglements (60 qumodes). Integrated microresonator-based optical frequency combs, heterogeneous photonic integration and near unity quantum efficiency photodiodes have been in the focus of research in the micro-photonics, optoelectronic and photonics device groups at UVA for many years. The project aims to combine these efforts and create a unique integrated device on a chip with multimode quantum emitter, qumodes processing and detection. Such a realization enables numerous quantum applications on a chip, including massively scalable cluster entanglement, scalable deterministic quantum processing, quantum secret sharing over QOFC, and quantum mode sorting.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.COLLEGE OF ST SCHOLASTICA INCCollege of Saint ScholasticaJennifer L Rosato(218) 723-6000Jrosato@css.eduRenee Fall09/19/2018$608,611$608,61110/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Broadening Participation and Building Pathways in Computer Science (CS) through Concurrent Enrollment1837723071508196071508196STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.gov1200 Kenwood AvenueDuluthMN55811-4199DuluthUS08College of Saint ScholasticaMN55811-4199DuluthUS08This project studies the implementation and outcomes of Concurrent Enrollment (CE) programs as a vehicle for broadening participation in high school to college pathways in Computer Science (CS). The Mobile Computer Science Principles (Mobile CSP) project at the College of St. Scholastica, an established curriculum endorsed by the College Board for its alignment with the Advanced Placement (AP) CSP framework, has formed a Research-Practitioner Partnership (RPP) with CE programs at Capital Community College in Hartford, Connecticut and Southwest Minnesota State University in Minnesota and with partner school districts in each state.
The RPP project explores whether CS through CE can broaden the high school to college pathway in computing disciplines for those traditionally underrepresented in these fields--female, underrepresented minority, and low-SES students. While the AP CSP course has enrolled a more diverse group of students than previous AP CS courses, it is not as diverse as other AP courses. CE programs appear to have better penetration than AP among schools that predominantly serve underrepresented minorities and low-SES students, showing promise for broadening participation in other disciplines and encouraging college matriculation.
By implementing and studying CS through CE in two different contexts (rural and low-SES in Minnesota and urban, diverse, and low-SES in Connecticut), the project contributes to transforming the educational pathways in CS in a variety of contexts and to understanding the supports and barriers to implementing CSP as CE with a broadening-participation goal. This project provides professional development and support of 40 high school teachers to teach a CE version of the Mobile CSP course among partnering school districts over the course of 3 years. The goals of this RPP project are (1) to examine and address the supports and barriers to implementing and sustaining Mobile CSP as a concurrent enrollment course and (2) to study whether a CE implementation of the CSP course broadens participation in computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.STONY CREEK COLORS, INC.Stony Creek Colors, IncShawn Genung(615) 756-4941shawn@stonycreekcolors.comNoah Fahlgren09/19/2018$750,000$750,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSTTR Phase II: Novel Analysis Tools for Production of Higher Indican Yielding Plants for Bio-based Indigo1831949078572363STTR PHASE IILinda Molnar(703) 292-0000lmolnar@nsf.gov411 Old Stone Bridge RdGoodlettsvilleTN37072-3204GoodlettsvilleUS05Stony Creek Colors, Inc921 Central AvenueSpringfieldTN37172-2873SpringfieldUS06This Small Business Technology Transfer (STTR) Phase II project will develop a new tool for the analysis of in situ indican precursor in indigo plants, which when combined with genomic analysis and genetic linkage mapping in selectively bred indigo crops, will lead to high indican yielding breeding parental lines and ultimately competitively price natural indigo dye. Additionally, characterization of genetic markers will accelerate further crop improvement by understanding and harnessing the genes crucial to indican synthesis and other aspects of significance to overall indigo yield. These advancements will benefit customers, denim mills, by leading to a more reliable, lower cost plant-derived indigo supply. The success of this multiphase STTR project will enable a cost-competitive, cleaner, and more sustainable denim dyeing process, while greatly expanding the market for domestically produced natural indigo. Commercialization of a more consistent and higher yielding US-grown indigo plant that produces high purity indigo powder can replace the current standard of synthetic, imported indigo powder. While in demand by the marketplace today, plant-derived indigo is currently only used in premium denim products due to the high cost per pound resulting from low yields per plant per acre. The direct result of this research will be to open new market segments and expand existing market penetration for US-grown and manufactured biobased indigo for the textile industry, an addressable market of $1.86B. The methods and technology developed through this project have a direct path to the commercial marketplace and the industry is ready to support biobased textile dyes such as plant-derived indigo.
During this project, reference genome resources will be constructed for indigo feedstock crops, F1 mapping populations will be constructed for P. tinctoria, I. tinctoria, and I. suffruticosa varieties, and design of the handheld rapid assay device will be validated through laboratory analysis. The reference genome for I. suffruticosa will be built using Pacific Biosciences SMRT sequencing and assembly. In addition to this reference genome, whole-genome resequencing will be performed on available I. suffruticosa and I. tinctoria varieties. Nucleotide variation and variant effect prediction will be made between the Indigofera-based indigo varieties. This variation will be used to develop markers to evaluate intervarietal crosses. Controlled greenhouse crosses of three species will be made to create F1 mapping populations for use in constructing a genetic map and linkage mapping, in combination with the resources developed. Intraspecies varieties exhibiting distinct phenotypic traits of commercial interest or notable dye yield differences will be selected for crossing to generate the F1 populations. Results from laboratory-based fluorometry equipment will be evaluated for efficacy and then compared against extractive indigo dye analysis from the leaf biomass. A final prototype will be constructed based on these findings and validated through use in the laboratory and in the field.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MISSOURI SYSTEMUniversity of Missouri-ColumbiaSuchismita Guha(573) 884-3687guhas@missouri.eduRainer Glaser, Ping Yu, Heather K Hunt, Guang Bian09/19/2018$352,346$352,34610/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of an ultrafast amplified laser system for nonlinear optics and time-resolved spectroscopic studies of condensed matter systems1827846153890272006326904MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.gov115 Business Loop 70 WCOLUMBIAMO65211-0001ColumbiaUS04University of Missouri-Columbia422 Physics Bldg.ColumbiaMO65211-0001ColumbiaUS04This Major Research Instrumentation award supports the acquisition of an ultrafast amplified laser system enabling studies at the intersections of condensed matter systems in physics, materials science and engineering, chemistry, chemical engineering, biology, and bioengineering. Probing materials with ultrafast short laser pulses captures some of the most fundamental physical processes that occur at extremely short timescales. These processes, which the project addresses, provide insights into charge transfer and evolution of optical excitations in solar cells, nonlinear optical phenomena in organic electronics, quantum materials, and (bio)organic materials, and transient optical processes in mesoporous materials. The ultrafast laser facility, while enhancing areas of nonlinear optics and time-resolved spectroscopic studies of condensed matter systems, complements existing research centers involved with nanomedicine, nanotechnology, and nanoscience at the University of Missouri (MU). The project seeks to make ultrafast laser technology available to a large user base at MU and in the state of Missouri. The versatility of the instrument and the transdisciplinary breadth of available expertise are unmatched in the region, empowering STEM students to obtain a competitive edge by hands-on experiences, and preparing them for employment in nanotechnology, biotechnology, materials science and engineering, and semiconductor-based academic research or industry. The research and educational activities are strengthened by the participation of students and researchers from Lincoln University, a Historically Black College & University in Missouri, and other institutions in the state along with advancing ongoing efforts in high school mentorship and middle school outreach programs.
Ultrashort light pulses open up new realms for probing nonlinear optical processes in materials and electronic devices. The proposed system is a versatile femtosecond laser system with broadband wavelength tunability and capabilities for multi-dimensional spectroscopy. It consists of three parts: (a) a femtosecond oscillator (mode-locked Ti-Sapphire laser); (b) a femtosecond amplifier; (c) a non-collinear optical parametric amplifier. The project focuses on investigating carrier dynamics and optical nonlinearities in electronic materials and organic semiconductor transistors to improve technology based on organic electronics. The research of two-dimensional (2D) materials, in particular the monolayer transition metal dichalcogenides, will benefit by obtaining in-depth understanding of the excitonic processes in these materials. In the area of molecular organic crystals, combined efforts in the second harmonic generation measurements, synthesis, and computational simulations will establish large scale polar order by rational design. The ultrafast laser system will be used to exploit the nonlinear optical properties of biological nanostructures in order to obtain multi-wavelength coherent sources with potential applications in nanophotonics. The project will further enable the development of silica-based materials by probing transient optical processes and fabricating micro- and nano-structures on the order necessary for their integration into optoelectronic devices. The proposed experimental laser facility will be bolstered by establishing a center for nonlinear optics, comprising both experimentalists and theorists, to promote research and educational activities in emerging ultrafast and nonlinear optical phenomena in condensed matter systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF BOSTON UNIVERSITYTrustees of Boston UniversityDouglas Holmes(617) 358-1294dpholmes@bu.eduHarold Park09/19/2018$531,503$531,50309/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITNatural Curvature and Soft Shells: Shape Shifting through Mechanical Instabilities1824882049435266049435266Mechanics of Materials and StrSiddiq Qidwai(703) 292-2211sqidwai@nsf.gov881 COMMONWEALTH AVEBOSTONMA02215-1300BostonUS07Trustees of Boston University730 Commonwealth Ave, EMA 213BostonMA02215-1300BostonUS07Nature uses internal stimuli to locally and globally change the curvature of thin and soft materials in a variety of ways. Natural curvatures occur in many biological and engineered structures through differential swelling, heating, or growth. They are: induced by proteins along a cell membrane, critical to the eversion of a developing Volvox embryo, and incurred in residually stressed composite plates and shells. Since natural curvature can drastically affect the morphology of thin bodies and induce mechanical instabilities, this provides a means for creating adaptive, shape-shifting structures capable of growing, morphing, and transitioning between complex shapes. This award supports fundamental research on the mechanics of instabilities induced by a natural curvature within thin shells. Harnessing these concepts for technological applications may enable the design of adaptive metamaterials, soft robotic actuators, and structural materials capable of programmatically controlled shape-shifting. Thus, this project will advance the science associated with mechanical instability; and advance the national health, prosperity, and welfare. This award also supports the further development of the digital inspiration, communication, and education (DICE) program. By placing an emphasis on visual, verbal, and written communication, this program will continue to enhance both the scientific communication of the next generation of scholars and broaden the participation of the general public through the creation and curation of open, online mechanics content.
This research will establish a fundamental understanding of how natural and spontaneous curvatures deform slender structures and soft materials. Its results will help engineer shells that are more robust against buckling, and facilitate the design of shells capable of changing between target shapes on command. The research will establish how natural curvature can provide shells with a knock-up factor against pressure buckling. The research team will utilize experiments that control curvature in soft materials through residual swelling in conjunction with a novel computational model based on a large deformation, rotation-free shell formulation. A fully nonlinear forward and inverse computational shell model to analyze shells with an evolving natural curvature will be developed and validated with experiments. Finally, an understanding of how locally applied natural curvatures deform soft shells will be established, enabling targeted shape-shifting that utilizes the computational modeling to inform the experimental design. This understanding may transform key technologies where shape-shifting materials are being intensely pursued for technological insertion, like soft robotics, deployable structures, and biomimetic design.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF WASHINGTONUniversity of WashingtonYoungjun Choe(206) 221-8908ychoe@uw.eduScott B Miles09/19/2018$508,631$508,63110/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITParticipatory Statistical Inference of Interdependent Critical Infrastructure Recovery Times1824681605799469042803536HDBE-Humans, Disasters, and thRobin Dillon-Merrill(703) 292-4921rdillonm@nsf.gov4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07University of WashingtonWA98195-0001SeattleUS07This research will develop new methods to estimate disaster recovery times of interdependent critical infrastructures, such as electricity and water systems, after damaging hazard events. Current recovery estimation is typically more ad hoc than systematic and statistically rigorous. This project will address this important challenge systematically and with rigor. It will lead to open-source tools for developing disaster recovery time estimates and planning for hazard-impacted critical infrastructure systems, with a focus on ensuring ease of use. Project case studies of the framework will underpin development of the tools, expand our understanding of infrastructure recovery after disasters, and help establish best practices that can be emulated by other communities. To build capacity of young researchers and future practitioners, the project team will integrate undergraduate and graduate students throughout the project. To engage traditionally underrepresented students in STEM education, the project team will leverage two existing programs targeting high school and incoming college students. This scientific research thus supports NSF's mission to promote the progress of science and to advance our national welfare and prosperity with benefits that will facilitate future planning initiatives to improve the resilience of United States communities and their critical infrastructure systems.
The project develops a new methodological framework, as well as software tools to support this framework, for estimating post-event interdependent critical infrastructure recovery times. The core of the framework is a participatory process for eliciting recovery estimates from topical experts. The framework will include tablet-based and web-based software tools to facilitate the elicitation. A human-centered approach will be used to develop the software to maximize user experience and elicitation performance. The methodological framework will use Bayesian inference to integrate available empirical data with expert estimates. Experts will estimate recovery functions or trends, rather than points or probability distributions. This will enable calculation of common resilience metrics, such as the area under a recovery curve. The framework and tools will be evaluated based on case studies in Seattle, WA and Portland, OR.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORKCUNY College of Staten IslandDwight H Richards(718) 982-3469Dwight.Richards@csi.cuny.eduNeophytos Antoniades, Xin Jiang, Eric J Harvey09/19/2018$350,000$350,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITGOALI: Collaborative Research: An Experimentally Validated Simulation Framework for Next-Generation Plastic Optical Fiber-based Systems on Airplanes1809242620128079073268849COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov2800 Victory BoulevardStaten IslandNY10314-6609Staten IslandUS11CUNY College of Staten Island2800 Victory BlvdStaten IslandNY10314-6609Staten IslandUS11GOALI: Collaborative Research: An Experimentally-Validated Simulation Framework for Next-Generation Plastic Optical Fiber-based Systems on Airplanes
This research project seeks to develop an experimentally-validated simulation framework that will help investigate and design Plastic Optical Fiber (POF)-based communication systems and networks for airplanes. The main participants are The College of Staten Island (CSI/CUNY), Montana State University-Bozeman (MSU), and The City College of New York (CCNY/CUNY). It will also involve an international collaboration with the University of Zaragoza (UZ), Spain, and a GOALI component with the world-leader in avionics, The Boeing Co. Avionic communication systems are currently undergoing a radical transformation in both the commercial and military sectors. The former (commercial), the focus of this project, exhibits an increasing need for high-speed communication due to emerging applications for the traveling public, as well as higher operational needs for the ultra-modern aircraft that are being deployed. In addition, aging aircraft wiring poses a significant threat to aircrafts, as electrical wires have proven to be one of the major factors leading to airplane failures. Therefore, there is an ongoing migration of avionic data buses from copper to fiber-based networks, since the latter exhibit high transmission capacity and high electromagnetic immunity. The investigators have suggested POF as a suitable transmission medium for next-generation avionic communication systems on commercial aircrafts due to its ease of handling, light weight and high tolerance to vibration, among other benefits. While experimental results have demonstrated the feasibility of high-speed data transmission over different types of POFs, the modeling and simulation of POF-based systems is lagging behind. Therefore, the investigators will develop a comprehensive set of components and simulation techniques that empower engineers to systematically explore different designs before settling on a final custom solution for their particular system. They will also make a special effort to involve women and underrepresented groups in the effort since they traditionally are not exposed to avionic systems engineering.
The goal of the project is to study the use of POF in an airplane environment with an emphasis on system performance and high bit rate transmissions. Glass fiber has a number of problems when used as a transmission medium in short-reach networks such as avionic networks. It is mechanically weak and generally lacks bending ability. Also, the core diameter of single-mode glass optical fiber is small (~10mm) and it requires very precise handling techniques. Plastic optical fiber (POF), even with its high loss (~100-300 dB/km) and diffusion, can solve these problems since it is easier to handle and has a bending radius of about 5 mm, which can be a big benefit in avionics networks. Its larger core diameter (50 mm to 1 mm) enables easy connections using inexpensive connectors. The increased core diameter allows higher tolerance to vibrations and to dust particles that can totally obstruct light propagation in glass fibers. The investigators will cover three different types of POF: large-core (up to 1 mm) step-index plastic optical fiber (SI-POF), multicore step-index plastic optical fiber (MC SI-POF), and graded-index plastic optical fiber (GI-POF). There are existing simulation models that capture all the guided modes in multimode fibers with detailed spatial fields; however, they are not adequate for large-core fibers, where there are millions of propagation modes. The project intends to develop computationally-efficient models that circumvent the need for prohibitively long simulation times and excessive computer memory. The model validation, a critical component of the project, will be done via a combination of the state-of-the-art device characterization laboratory at the University of Zaragoza and a testbed at the College of Staten Island. Montana State University will primarily work on advanced modulation formats and digital signal processing algorithms. Boeing Co. will provide prototype devices and realistic system designs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.INCORPORATED RESEARCH INSTITUTIONS FOR SEISMOLOGYIncorporated Research Institutions for SeismologyRobert S Detrick(202) 682-2220detrick@iris.eduJohn Taber, Timothy K Ahern, Robert L Woodward09/19/2018$89,509,501$17,200,00009/01/201808/31/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth System Dynamics: Seismological Facility for the Advancement of Geoscience (SAGE) - EAR Scope1851048183277938183277938SAGEMargaret Benoit(703) 292-0000mbenoit@nsf.gov1200 New York Avenue, NWWashingtonDC20005-6142WashingtonUS00Incorporated Research InstitutionsDC20005-6142WashingtonUS00The IRIS (Incorporated Research Institutions for Seismology) Consortium will develop, operate, and maintain a distributed, multi-user facility entitled Seismological Facilities for the Advancement of Geoscience (SAGE). Expert professional staff, with guidance provided by the scientific community, will manage and operate a set of foundational capabilities that are essential for current research support, as well as frontier activities that will enable future research. The facility will promote advances in our understanding of Earth structure and dynamics, earthquakes and volcanic eruptions, and interactions between the solid Earth, hydrosphere, and atmosphere through management and operation of: 1) Global and regional continuously operating seismic networks, including the Global Seismographic Network; 2) Portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences. The seismological facilities provided through the SAGE contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; national security; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data and data products from SAGE will be used by state and federal agencies including the United States Geological Survey, National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, Department of Energy, and Department of Defense, for mission agency activities, including earthquake monitoring and characterization, tsunami warning, weather forecasting, water and environmental management, and nuclear test monitoring. SAGE programs will also support inquiry-based science education, enhancing students' abilities to engage directly with science and engineering principles and practice, and enabling them to pursue STEM careers in academia, industry, business, and government. The SAGE outreach activities promote public engagement and science literacy.
The SAGE facility provides instrumentation services; data services; and education, workforce development, and community engagement activities in support of seismology. Researchers use SAGE to gain valuable insights into fundamental Earth processes, and SAGE also provides key data for national security needs, including monitoring efforts of clandestine nuclear tests. The scientific priorities of the new facility would enable advances in the following areas: (1) Global Earth Structure and Dynamics: The facility would enhance our ability to resolve the three-dimensional structure of the Earth's interior and enable investigators to study processes that drive plate tectonics and natural hazards such as earthquakes, tsunamis, and volcanic eruptions. (2) Fault Zones and the Earthquake Cycle: Over the last decade, scientists have discovered a broad array of fault zone slip behaviors that span a wide variety of temporal and spatial scales. The SAGE facility will enable a variety of seismic and electromagnetic measurements to elucidate how these different types of behaviors start and stop, vary along fault zones, and interact with one another. (3) Magmas and Volatiles in the Crust and Mantle: Geophysical instrumentation is critical for understanding volcanic systems and minimizing risks associated with volcanic hazards. The capabilities provided by SAGE will enable researchers to study melt production, monitor its transport through the crust, and map out the plumbing systems of volcanoes. (4) Hydrosphere, Cryosphere, and Atmosphere: An area of increasing community interest is utilizing geophysical measurements to study processes at the Earth's surface. The SAGE facility will provide opportunities to study processes in the near-surface, such as hydrology, cryospheric processes, and glacier dynamics. (5) Education, Public Outreach, and Workforce Development: SAGE will develop a variety of educational resources and enable hundreds of undergraduate research opportunities. A major focus of the SAGE activities will be on broadening participation of underrepresented students through IRIS' new Urban Geosystems focus. Additionally, the facility will develop animations, simulations, and other visualizations of Earth processes to help instructors at all level teach about Earth Science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK, THEColumbia UniversityIoannis Kymissis(212) 854-6851johnkym@ee.columbia.eduPatricia J Culligan09/19/2018$275,881$275,88110/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER SitS: Signaling the Health Of Tree-pit Soil (SHOTS)1841615049179401049179401ECI-Engineering for Civil InfrRichard J. Fragaszy(703) 292-7011rfragasz@nsf.gov2960 BroadwayNEW YORKNY10027-6902New YorkUS10Columbia University550 West 120th StreetNew YorkNY10027-6601New YorkUS10This EArly-concept Grant for Exploratory Research (EAGER) Signals in the Soil (SitS) award is a high risk/high return research project that could provide essential data for the modeling of rainwater infiltration in urban areas needed in the design and operation of green infrastructure for storm water management. As a result of high land surface coverage by buildings, pavement, parking lots, and other impervious surfaces, a typical city block generates five times as much stormwater runoff during wet-weather flow than a woodland area of the same size. This runoff, which contains pollutants including oils, heavy metals, particulates and nutrients, is responsible for the impairment of urban water bodies throughout the world. In the United States, stormwater runoff is the leading source of coastal zone pollution, and the third largest source of lake and inland water body pollution. Urban soils can soak up rain that falls within city boundaries, and thus help mitigate the adverse impacts of stormwater runoff. Nonetheless, the ability of urban soils to infiltrate rainwater is dependent on soil ecosystem health. Prior investigations into factors influencing urban soil ecosystem health have primarily involved manual sampling of soils followed by laboratory analysis. This has made it difficult to amass the number of observations needed, over both space and time, to fully understand the complexities of urban soil ecosystems. Without a better understanding of soil ecosystem behavior, it is difficult to develop strategies for managing urban soils in ways that maximize their capacity to reduce urban stormwater runoff. This project is an interdisciplinary collaboration between an expert in unconventional and advanced electronics (Kymissis) and an expert in geo-environmental engineering and urban sustainability (Culligan) to enable proof of concept for a wireless, low-power, in situ soil sensing system that has significant potential for soil ecosystem monitoring across a wide-range of settings. The new soil sensing system will be field-tested in urban soils located in New York City.
The in situ sensors comprise of miniature, low-powered, wireless sensors under development in the Kymissis lab. These low-cost systems use the circuit board as an integral mechanical element, and incorporate capacitance sensing for non-contact moisture monitoring, temperature monitoring, advanced power management, and Bluetooth wireless communication for relaying information back to a readout computer. The next generation system to be developed by this project will also add pH and dissolved oxygen (DO) measurements, enabling the sensors to measure indicators of the physical, chemical and biological health of soils. The sensing system will be used to monitor soils located in 40 urban tree pits within the Morningside Heights neighborhood of New York City. Culligan has prior, manually collected, data on relationships between the water infiltration capacity of these soils and tree pit design and management features. The data gathered from the sensors will be compared to this prior data to validate the performance of the new sensing system. Sensor data will also be used to advance understanding of the factors influencing urban soil ecosystem services. The research program is ideally suitable for involvement of local communities in citizen science activities which directly relate to stormwater management in their neighborhood.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CALIFORNIA, SAN DIEGOUniversity of California-San DiegoJoel P Conte(858) 822-4545jpconte@ucsd.eduJ E Luco, Jose Restrepo, Tara C Hutchinson, Yael Van Den Einde09/19/2018$16,299,996$8,500,00010/01/201809/30/2021Cooperative AgreementsNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITNatural Hazards Engineering Research Infrastructure: Upgrade of the Large High Performance Outdoor Shake Table to Six Degrees of Freedom1840870804355790071549000Natural Hazards Engineering ReJoy Pauschke(703) 292-7024jpauschk@nsf.govOffice of Contract & Grant AdminLa JollaCA92093-0621La JollaUS49University of California-San DiegoLa JollaCA92093-0934La JollaUS49The large, high-performance, outdoor shake table (LHPOST) experimental facility at the University of California, San Diego, is the largest facility of its kind in the United States for conducting earthquake engineering research on civil infrastructure, and has the world's largest payload capacity (20 MN). Because there are no overhead height restrictions, this facility can accommodate the tallest structures ever tested on any shake table. The LHPOST, originally designed to accommodate six degrees of freedom (6DOF), was supported for construction during 2002-2004 as a single degree of freedom (SDOF) system, by the National Science Foundation (NSF), Network for Earthquake Engineering Simulation (NEES), Major Research Equipment and Facilities Construction account, due to budgetary constraints. As an SDOF system and a multi-user national research facility, the LHPOST has been supported by NSF for operations and maintenance under the NEES (FY 2005-FY 2014) and the Natural Hazards Engineering Research Infrastructure (NHERI) (FY 2015 to date) programs. This award will upgrade the LHPOST from its current SDOF configuration to a full 6DOF capability. In its upgraded configuration, the LHPOST will be able to reproduce all six components of motion (two horizontal and vertical translational components, as well as pitch, roll, and yaw rotational components) experienced by the ground during earthquakes. It will provide a one-of-a-kind facility to test large to full size civil infrastructure, such as structural, nonstructural, geo-structural and soil-foundation-structural systems, under strong earthquake excitation. The ability to test infrastructure under the full range of combined horizontal, vertical, and rotational seismic input motion is critical for research that can lead to effective, economical,and practical new infrastructure designs, as well as seismic rehabilitation and retrofit strategies for existing infrastructure, to improve the seismic performance for post-earthquake resilience, public safety, and national welfare. The 6DOF LHPOST will provide critical landmark datasets to support the development, calibration, and validation of high-fidelity, physics-based computational models of civil infrastructure systems that will progressively shift the current reliance on physical testing to model-based simulation for the seismic design and performance assessment of such systems. The experimental capabilities provided by the 6DOF LHPOST will support U.S. leadership in earthquake engineering research. The upgraded shake table will also provide a unique tool to educate graduate, undergraduate, and K-12 students, as well as the news media, policy makers, infrastructure owners, insurance providers, and the public, about natural disasters and the national need to develop effective technologies and policies to prevent earthquakes from becoming societal disasters. This award supports the National Earthquake Hazards Reduction Program (NEHRP).
The upgrade of the LHPOST to 6DOF will be achieved by adding two horizontal actuators and reconfiguring all four horizontal actuators into a V-shape at both longitudinal ends of the shake table's 12.2 meter long by 7.6 meter wide platen to provide bi-axial horizontal motions, as well as the yaw motion capabilities. Each of the existing six pressure balanced vertical actuators/bearings will be equipped with a high-flow servovalve to enable vertical, pitch, and roll motion capabilities. To operate the 6DOF table, the number of hydraulic power units will be increased from two to four and the total size of the accumulator banks will be increased from 9,500 to 37,800 liters. A new piping system will be installed between the accumulator banks, the horizontal and vertical actuators, and the surge tank. A third nitrogen-filled hold-down strut will be installed between the bottom of the platen and the bottom of the reaction block to increase the overturning moment capacity of the table. The existing SDOF shake table controller (both hardware and software) will be replaced by a controller with 6DOF capabilities. A new hydraulic distribution system controller will also be provided to handle the safety interlocks, control of the hydraulic power units, and control of the accumulator charging and blowdown. Additionally, the height of the existing four safety towers will be doubled to protect the hydraulic power building from potential specimen collapse. During the upgrade, operations of the shake table under NHERI will cease for a period of 14 months between mid-2020 and mid-2021. Before reopening the facility for operations and research, commissioning of the facility, including acceptance and characterization tests, will be performed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PRESIDENT AND FELLOWS OF HARVARD COLLEGEHarvard UniversityNa Li(626) 600-6196nali@seas.harvard.eduDavid C Parkes09/19/2018$250,000$250,00010/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Learning, Selection, and Control in Residential Demand Response for Grid Reliability1839632082359691001963263ENERGY,POWER,ADAPTIVE SYSAnthony Kuh(703) 292-2210akuh@nsf.gov1033 MASSACHUSETTS AVECambridgeMA02138-5369CambridgeUS05President and Fellows of Harvard College33 oxford street MD 345CambridgeMA02138-2933CambridgeUS05As renewable energy sources increase and conventional generators retire, demand response (DR) has been utilized to address the reliability issue on balancing real-time demand and supply in power grids. However, the potential of residential DR, which is the largest share of electricity demands, has not been fully exploited in practice. Existing pilots reveal many issues, such as i) small monetary rewards which play a limited role in user participation, ii) user dissatisfaction when utility companies exploit DR resources extensively, and iii) the lack of reliability due to the unpredictability of user behavior. In collaboration with ThinkEco Inc, this proposal will develop novel and applicable approaches for residential DR with provable guarantees. The method will learn DR behavior, select the correct residential users, and automatically control residential appliances -- all in the service of enhancing system reliability. The research will be tested and validated on real-world residential DR programs using ThinkEco platforms. The research results will advance real-time learning for human-in-the-loop societal systems with applications ranging from transportation to power grids to AI-enabled systems of the future. The team is strongly committed to providing opportunities in STEM to K-12, women, and under-represented minorities. Moreover, the close collaboration between academia and industry promises a fast and effective transition of academic results to industry practice.
Specifically, by understanding users' energy consumption behavior from both historical and real-time measurements, and adjusting user selection and control strategies in real-time, this proposed research will invent DR learning and control mechanisms to satisfy various power grid operation requirements. A major theme in this proposal is to close the loop between learning (exploration) and control (exploitation) in human-in-the-loop societal systems: how to learn (explore) user behavior while taking good control actions (exploitation) at the same time. There is a fundamental tradeoff between exploration and exploitation, and the proposed research aims to uncover the tradeoff and design real-time decision-making rules to achieve near-optimal performance for residential DR. Different from the conventional approaches to learning in computer science or statistics, this proposal aims to tackle the challenge of intertwined interactions between human users and the engineered systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ASSOCIATION OF UNIVERSITIES FOR RESEARCH IN ASTRONOMY, INC.Association of Universities for Research in Astronomy, Inc.Charles Mattias Mountain(202) 483-2101nsfnotifications@aura-astronomy.org09/19/2018$25,974,117$12,987,06010/01/201812/31/2022Cooperative AgreementsNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITGemini Observatory in the Era of Multi-Messenger Astronomy: High Image Quality and Rapid Response to Cosmic Events1839225057905887057905887GEMINIChristopher Davis(703) 292-4910chrdavis@nsf.gov1331 Pennsylvania Ave. NWWashingtonDC20004-0000US00AURA, Inc. - Gemini Observatory670 N. A'ohoku PlaceHiloHI96720-9999HiloUS02The Gemini Observatory operates two large telescopes, one in Hawai'i and one in Chile. These two telescopes provide astronomers in the U.S., Canada, Argentina, Brazil, and Chile with access to the whole sky. Using modern instruments on each telescope, astronomers are able to study everything from asteroids, comets and nearby planets, to huge super-bright stars and distant galaxies. Plans are now under way at Gemini to prepare each telescope for a new decade of discovery. Astrophysics in the 2020s will be revolutionized by "Multi-Messenger Astronomy", an exciting new field that uses gravitational waves and high-energy particles, as well as ordinary everyday light, to study some of the most exotic objects and explosive events in the Universe. Facilities like NSF's Laser Interferometer Gravitational-Wave Observatory (LIGO), the NSF/University of Wisconsin IceCube South Pole Neutrino Observatory, and NSF's latest telescope, the Large Synoptic Survey Telescope (LSST), will detect these "messengers", changing the way we study the Universe. In support of these remarkable new observatories, Gemini will develop new computer software and new optics hardware so that astronomers can study each new discovery quickly and in high detail. In addition to making remarkable discoveries and doing amazing science, Gemini is also a leader in education, public information and outreach activities. Gemini staff bring science to the communities in both Hawai'i and Chile through unique programs such as Journey through the Universe, AstroDay, and Viaje al Universo. With this new award they will extend their reach by developing a Planetarium show that will help the public better understand Multi-Messenger Astronomy. Gemini will also run workshops for educators and communicators so that they too can explain the exciting new discoveries that will surely be made by LIGO, IceCube, LSST and Gemini over the coming decade.
Gemini has proposed a challenging though very exciting program of cutting-edge development activities that are in line with NSF's strategic goals and those of its international partners in the Gemini Observatory. The enhancement of existing Adaptive Optics (AO) capabilities at Gemini-S and particularly Gemini-N on Maunakea, one of the best sites in the world for high-resolution imaging, will ensure that the observatory remains competitive in the 2020s, in the run-up to the commissioning of 30-to-40 meter class telescopes at the end of the coming decade. Wide-field AO-corrected infrared imaging at Gemini will complement a similar capability on the James Webb Space Telescope, which will hopefully be executing its prime mission in the 2020s. At the same time, in collaboration with other national facilities, Gemini staff will develop and mature software aimed specifically at preparing Gemini for time domain and multi-messenger astronomy in a decade when LIGO and LSST will drive many of the most exciting science discoveries. The proposal's goal of ensuring that Gemini is the best positioned public 8-meter class facility for follow-up activities is clearly consistent with the wishes of the observing communities at home and abroad.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BOARD OF TRUST OF COMMUNITY TECHNICAL COLLEGECapital Community CollegeSeth R Freeman(860) 906-5249sfreeman@ccc.commnet.eduKaren Binkhorst09/19/2018$183,654$183,65410/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Broadening Participation and Building Pathways in Computer Science (CS) through Concurrent Enrollment1836983784363330STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.gov950 Main StreetHartfordCT06103-1234HartfordUS01Capital Community College950 Main StreetHartfordCT06103-1207HartfordUS01This project studies the implementation and outcomes of Concurrent Enrollment (CE) programs as a vehicle for broadening participation in high school to college pathways in Computer Science (CS). The Mobile Computer Science Principles (Mobile CSP) project at the College of St. Scholastica, an established curriculum endorsed by the College Board for its alignment with the Advanced Placement (AP) CSP framework, has formed a Research-Practitioner Partnership (RPP) with CE programs at Capital Community College in Hartford, Connecticut and Southwest Minnesota State University in Minnesota and with partner school districts in each state.
The RPP project explores whether CS through CE can broaden the high school to college pathway in computing disciplines for those traditionally underrepresented in these fields--female, underrepresented minority, and low-SES students. While the AP CSP course has enrolled a more diverse group of students than previous AP CS courses, it is not as diverse as other AP courses. CE programs appear to have better penetration than AP among schools that predominantly serve underrepresented minorities and low-SES students, showing promise for broadening participation in other disciplines and encouraging college matriculation.
By implementing and studying CS through CE in two different contexts (rural and low-SES in Minnesota and urban, diverse, and low-SES in Connecticut), the project contributes to transforming the educational pathways in CS in a variety of contexts and to understanding the supports and barriers to implementing CSP as CE with a broadening-participation goal. This project provides professional development and support of 40 high school teachers to teach a CE version of the Mobile CSP course among partnering school districts over the course of 3 years. The goals of this RPP project are (1) to examine and address the supports and barriers to implementing and sustaining Mobile CSP as a concurrent enrollment course and (2) to study whether a CE implementation of the CSP course broadens participation in computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF CALIFORNIA, THEUniversity of California-BerkeleyAaron R Parsons(510) 406-4322aparsons@astro.berkeley.eduDavid Robert DeBoer09/19/2018$7,173,107$4,173,10710/01/201809/30/2023GrantNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITHERA: Unveiling the Cosmic Dawn1836019124726725071549000MID-SCALE INSTRUMENTATIONRichard E. Barvainis(703) 292-4891rbarvai@nsf.govSponsored Projects OfficeBERKELEYCA94704-5940BerkeleyUS13University of California-Berkeley455 Campbell HallBerkeleyCA94720-3411BerkeleyUS13Humanity's quest to understand the Universe and our place in it has led to some of the hallmark scientific and technical achievements of our time. These include the discovery of the Cosmic Microwave Background, the discovery of the accelerating expansion of the Universe, and the use of a variety of observational techniques to characterize the cosmology of the Universe. Scientists have measured the six key cosmological parameters that govern the geometry of the Universe with great precision, but they have not yet connected the dots to understand how the seeds of early structure from the Big Bang evolved into the stars, galaxies, and black holes seen today in the local Universe. In particular, there are very few observations of a period known as the "Cosmic Dawn" when the Universe was approximately 100 to 1000 million years old. During the Cosmic Dawn, the first stars and galaxies formed out of a pristine hydrogen gas that was synthesized during the Big Bang. As stars lit up, burned, and exploded in supernovae, the energy they released started to heat and then ionize the hydrogen that was not yet trapped in galaxies. Today, astronomers observe that nearly all hydrogen between galaxies has been re-ionized into a plasma state. The time when this happened is called the Epoch of Reionization. This project will use the Hydrogen Epoch of Reionization Array (HERA), a purpose-built telescope, to measure and characterize the Universe from the Cosmic Dawn to the Epoch of Reionization, to fill in this critical gap. Astronomy has broad interest throughout society and serves as an excellent introduction to science and technology for young people. In order to bring this impact to under-served students HERA has instituted an undergraduate outreach program called CHAMP, which serves as a significant summer internship program for underrepresented minorities at HERA partner institutions.
HERA is an international project with Partners in the US, UK, Canada, Italy and South Africa. The telescope is well under construction in the Karoo region of Northern Cape South Africa at the South African Radio Astrophysical Observatory's Karoo Astronomy Reserve. Starting in 2019, HERA will comprise 350 14-m antennas in close proximity to one another and operate from 50-250 MHz. The Karoo location has been established as a special "radio-quiet" zone, meaning that efforts are undertaken to minimize the impact of the radio frequency emission that humans generate through our technology. Currently operational, HERA is measuring the emission due to the red-shifted hyperfine transition of hydrogen gas, which has a rest frequency of 1420 MHz. The expansion of the Universe redshifts these frequencies down to 50-250 MHz at the age of the Universe expected for the Cosmic Dawn and Epoch of Reionization. Given the expected structure of the gas over these redshifts, the signal is expected to be spectroscopically distinguishable from the much brighter foreground, which is predominantly spectrally smooth emission from our Galaxy's synchrotron radiation. Given its sensitivity and special-purpose design, HERA is expected to accurately measure the reionization fraction over this span of epochs. This measurement will allow us to understand the cosmology and astrophysics of the Universe over this transitional portion of its history.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.INKSPACE IMAGING, INC.InkSpace Imaging, Inc.Pierre B Lechene(626) 807-9276b.lechene@inkspaceimaging.com09/19/2018$750,000$750,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: A suite of flexible printed MRI coils for newborn to adult patients1831253080330758SMALL BUSINESS PHASE IIBen Schrag(703) 292-8323bschrag@nsf.gov279 Rheem BoulevardMoragaCA94556-1540MoragaUS11University of California BerkeleyCory HallBerkeleyCA94720-0001BerkeleyUS13This Small Business Innovation Research (SBIR) Phase II project aims to develop a suite of screen-printed receive coils for Magnetic Resonance Imaging (MRI), that are flexible, lightweight, low-cost and adapted to the entire population from infants to adults. MRI is widely used to establish a broad variety of clinical diagnosis, but suffers from long examination times and a high rate of failure, resulting in a yearly loss of more than $4 billion in the United States alone. Printed receive coils are extremely flexible, lightweight, and conform well to the human body. With this technology, coils can be designed and manufactured inexpensively to fit all patient sizes, thus improving image quality and enabling robust acceleration of the method. These benefits can contribute to increase the success rate of MRI exams, speed up procedure time, enhance the clinical workflow, and reduce equipment costs. Printed coils will improve the quality of care offered by MRI suites and increase the availability and use of MRI to a wider patient population. Overall, this project will develop a clinical-ready system capable of delivering the full economic and clinical benefits of printed coils, which will contribute to a reduction of the healthcare costs associated with MRI.
This project aims to fully realize a clinical-ready system consisting of a collection of printed, flexible lightweight MRI coil arrays, and connecting to a single universal cable to interface with the MRI scanner. A first part of the project will focus on the design of the cable and the associated connection scheme allowing interchange of multiple printed coil arrays of different sizes. Different strategies will be examined with the intent of maintaining high performance and safety while maximizing the advantages brought by printing. A second project goal will focus on the development of a collection of printed coil arrays for patient sizes ranging from newborn to adult, that are compatible with the universal cable and for both 3T and 1.5T scanners. The arrays will be designed for body imaging and will consist of 32-channel devices divided into 16-channel posterior and anterior portions. Their performance will be compared to a commercial 32-channel product. The final system will meet all the safety requirements for medical use and will be ready to be manufactured at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PENNSYLVANIA STATE UNIVERSITY, THEPennsylvania State Univ University ParkMichael Hillmanmzh226@psu.eduJing Du09/19/2018$545,418$545,41810/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITAn Integrated Computational-Experimental Approach to Three-dimensional Fracture in Polymer-Ceramic Composites1826221003403953003403953Mechanics of Materials and StrSiddiq Qidwai(703) 292-2211sqidwai@nsf.gov110 Technology Center BuildingUNIVERSITY PARKPA16802-7000University ParkUS05Pennsylvania State Univ University Park110 Technology Center BuildingUniversity ParkPA16802-7000University ParkUS05Composite materials are used in spacecrafts, aircrafts, automobiles, and naval vessels for their unique property to provide high strength- and stiffness-to-weight ratios. They are also used in bioengineering and electronic devices; and concrete is a composite that is one of the most widely used materials today. Understanding their behavior is important to advance the design of these materials, as measures taken to further strengthen or stiffen them can sometimes yield counterintuitive or even counterproductive results. This award supports fundamental research on understanding the material properties of composites by examining the three-dimensional mechanics and failure evolution on the microstructural level. An integrated combination of experiments and simulations will be used to study their behavior, with a focus on polymer-ceramic composites. This project will answer fundamental questions about the competing mechanisms on the microscale that lead to the counterintuitive relations between microstructure and resulting composite properties. The new knowledge and tools will lead to advances in the design of composites, and significantly impact the broad range of applications in which these materials are used, thereby impacting national health, prosperity, and welfare; and securing the national defense. The outreach and educational activities in this project will broaden the participation of undergraduate and graduate students, particularly women and from other underrepresented groups, in STEM subjects through research in the PIs' labs. The outreach activities with visiting students from Africa also intends to inspire interest of African-American students in STEM subjects.
A new computational approach called the continua-discontinua particle method (CDPM) is proposed which combines the strengths of traditional continuum-based methods in fundamental mechanics and mathematically grounded principles, with the strengths of discrete methods in simulating arbitrary complex three-dimensional fracture. The method allows the transition under failure from a meshfree particle discretization based on continuum mechanics, to that of a discrete fracture network similar to discrete particle methods. An approach using micro X-ray computed tomography (micro-CT) and an in-situ mechanical tester is proposed, which yields 3D full-field mechanical measurements. Other material characterization methods, such as tensile testing, nanoindentation, and scanning electron microscopy will also be employed to compliment the in-situ experiments. The experiments and simulations will be closely integrated to both formulate and validate the numerical models for prediction of composite stiffness, strength, and toughness of polymer-ceramic composites with varying filler morphology, as well as illuminate the underlying causes of the structure-property relationships in these materials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF PITTSBURGH THEUniversity of PittsburghSachin S Velankar(412) 624-9984velankar@pitt.eduEdith Tzeng09/19/2018$341,599$341,59910/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITThe Dynamic Topography of the Blood-Contacting Surface of Arteries1824708004514360004514360Biomechanics & MechanobiologyMichele Grimm(703) 292-4641mgrimm@nsf.govUniversity ClubPittsburghPA15213-2303PittsburghUS14University of PittsburghUniversity ClubPittsburghPA15213-2303PittsburghUS14When segments of arteries are removed from the body, they have a distinct, corrugated appearance on the inside. It has long been assumed that this is a result of the artery deflating as the effect of blood pressure is removed. The investigators in this project hypothesize that the corrugations actually play a role in normal, physiological function and that they change significantly due to normal changes in arterial pressure and diameter. This hypothesis will be studied through a combination of experimental and modeling techniques. The researchers will answer questions about the underlying biomechanics of these corrugations as well as how they vary with normal physiological function and along the length of the arterial structure within the body. The knowledge gained will significantly impact fundamental understanding of arterial biomechanics and their physiological function. It may also inform future development of improved replacement arterial graft designs for treatment of injured or diseased arteries. The research will be conducted by a unique research team that includes medical residents as well as graduate and undergraduate students. This will support the engineers ability to connect the engineering research to the actual physiology and potential clinical impact. In addition, modules on arterial mechanics and the underlying materials performance will be developed as part of a series of lecture-demonstration activities that provide K12 students with a visual understanding of the science.
Three aims have been established to test the stated hypothesis. First, the team will investigate the biomechanics of the luminal corrugations by treating the internal elastic lamina (the inner surface) as a thin, nearly-inextensible membrane in contact with a soft substrate. Second, the dynamic topography of the arteries will be investigated to understand the state of the corrugations under normal physiologic conditions. Finally, the variation in luminal structure and corrugations will be investigated for arteries as they move distal to (away from) the heart. This work will use a combination of imaging and biomechanical testing strategies in both in vivo and excised arteries from porcine specimens, and the biomechanical behavior will be related to the collagen and elastin microstructure. The experiments will be partnered with finite element models that will be used to understand the underlying mechanisms of the biomechanical behavior as well as, once validated, investigate varying loads and boundary conditions that cannot easily be studied experimentally. If the primary hypothesis is supported, the investigators plan to link their findings to the secondary hypothesis that the functional role of the corrugations is to protect the endothelial layer of the artery by allowing it to accommodate the arterial diameter changes without in-plane stretching.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY CORPORATION FOR ATMOSPHERIC RESEARCHUniversity Corporation For Atmospheric ResAntonio J Busalacchi(303) 497-1652tonyb@ucar.edu09/19/2018$499,999,999$5,900,00010/01/201809/30/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITThe Management and Operation of the National Center for Atmospheric Research1755088078339587078339587NAT CENTER FOR ATMOSPHERIC RESSarah L. Ruth(703) 292-8521sruth@nsf.gov3090 Center Green DriveBoulderCO80301-2252BoulderUS02University Corporation For Atmospheric Res3090 Center Green DriveBoulderCO80301-2252BoulderUS02The National Center for Atmospheric Research (NCAR) is an NSF Federally Funded Research and Development Center. NCAR's mission is: to understand the behavior of the atmosphere and related Earth and geospace systems; to support, enhance, and extend the capabilities of the university community and the broader scientific community, nationally and internationally, and to foster the transfer of knowledge and technology for the betterment of life on Earth. NCAR fulfills this mission with tightly integrated programs organized around three overlapping primary areas of activity: cutting edge airborne and ground-based observational facilities, community weather, and climate models with many thousands of users, and petascale high-performance computing. These are accompanied by a broad portfolio of programs supporting education, career development, public engagement, and increasing diversity in the geosciences. This award funds the University Corporation for Atmospheric Research (UCAR) to manage and operate NCAR on behalf of NSF.
Understanding the Earth system is among the most exciting and important scientific challenges of our time - from the drivers of hazardous weather events that cost the nation tens of billions of dollars in damage each year to the longer-term impacts of climate change on the water cycle, water availability, and weather extremes. Under UCAR's management, NCAR will work with the broader scientific community to observe, understand, and ultimately predict the evolution of the atmosphere and related components of the Earth system at greater time and finer spatial scales. Ultimately, these advances will improve our nation's ability to protect lives and property, enhance the American economy, and support national security.
Building upon its strong stewardship of NCAR since 1960, UCAR aims to ensure that NCAR continues to be a community leader and preeminent National Center that advances the atmospheric and Earth system science communities by conducting fundamental and transformative research at the frontiers of knowledge. UCAR will operate, maintain and develop NCAR's state-of-the-art observational, computational, and modeling facilities and services. UCAR will support NCAR by recruiting, developing, and retaining an expert and increasingly diverse workforce for the National Center. UCAR will also promote an ambitious and inclusive program of research, education, and outreach to serve the scientific community, and is moving aggressively to increase diversity and inclusiveness in its culture and in STEM education for the geosciences workforce. UCAR's vision includes identifying future requirements; developing compelling NCAR strategic plans; involving the community in planning, implementation and review; providing effective and efficient performance-based management of resources; making strategic investments in NCAR; creating an environment that attracts and retains exceptional talent; and enabling new partnerships that advance the science. UCAR brings a unique governance structure through its 117 members and many academic, government, and industry partners that will strengthen and promote NCAR to represent broad national and international interests.
Under this award, it is anticipated that NCAR will maintain a leadership role in creating objective information in support of national and international decisions on mitigation, adaptation, resiliency, and sustainability; and engaging interactively with the consumers of its science. This will result in improved prediction capabilities and more effective application of these advances to societal needs. Because UCAR's governance is based in academia, its management structure facilitates the development of future diverse scientists, provides access to world-leading facilities and exciting research opportunities for students, and engages the public through successful outreach program. UCAR's policy of free and open exchange of ideas, data, models, observational instruments and platforms, and information will maximize the impacts of the Center's research, development, and educational activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.INCORPORATED RESEARCH INSTITUTIONS FOR SEISMOLOGYIncorporated Research Institutions for SeismologyRobert S Detrick(202) 682-2220detrick@iris.eduJohn Taber, Timothy K Ahern, Robert L Woodward09/19/2018$1$110/01/201809/30/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth System Dynamics: Seismological Facility for the Advancement of GEoscience (SAGE)1724509183277938183277938INSTRUMENTATION & FACILITIESMargaret Benoit(703) 292-0000mbenoit@nsf.gov1200 New York Avenue, NWWashingtonDC20005-6142WashingtonUS00Incorporated Research Institutions for SeismologyDC20005-6142WashingtonUS00The IRIS (Incorporated Research Institutions for Seismology) Consortium will develop, operate, and maintain a distributed, multi-user facility entitled Seismological Facilities for the Advancement of Geoscience (SAGE). Expert professional staff, with guidance provided by the scientific community, will manage and operate a set of foundational capabilities that are essential for current research support, as well as frontier activities that will enable future research. The facility will promote advances in our understanding of Earth structure and dynamics, earthquakes and volcanic eruptions, and interactions between the solid Earth, hydrosphere, and atmosphere through management and operation of: 1) Global and regional continuously operating seismic networks, including the Global Seismographic Network; 2) Portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences. The seismological facilities provided through the SAGE contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; national security; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data and data products from SAGE will be used by state and federal agencies including the United States Geological Survey, National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, Department of Energy, and Department of Defense, for mission agency activities, including earthquake monitoring and characterization, tsunami warning, weather forecasting, water and environmental management, and nuclear test monitoring. SAGE programs will also support inquiry-based science education, enhancing students' abilities to engage directly with science and engineering principles and practice, and enabling them to pursue STEM careers in academia, industry, business, and government. The SAGE outreach activities promote public engagement and science literacy.
The SAGE facility provides instrumentation services; data services; and education, workforce development, and community engagement activities in support of seismology. Researchers use SAGE to gain valuable insights into fundamental Earth processes, and SAGE also provides key data for national security needs, including monitoring efforts of clandestine nuclear tests. The scientific priorities of the new facility would enable advances in the following areas: (1) Global Earth Structure and Dynamics: The facility would enhance our ability to resolve the three-dimensional structure of the Earth's interior and enable investigators to study processes that drive plate tectonics and natural hazards such as earthquakes, tsunamis, and volcanic eruptions. (2) Fault Zones and the Earthquake Cycle: Over the last decade, scientists have discovered a broad array of fault zone slip behaviors that span a wide variety of temporal and spatial scales. The SAGE facility will enable a variety of seismic and electromagnetic measurements to elucidate how these different types of behaviors start and stop, vary along fault zones, and interact with one another. (3) Magmas and Volatiles in the Crust and Mantle: Geophysical instrumentation is critical for understanding volcanic systems and minimizing risks associated with volcanic hazards. The capabilities provided by SAGE will enable researchers to study melt production, monitor its transport through the crust, and map out the plumbing systems of volcanoes. (4) Hydrosphere, Cryosphere, and Atmosphere: An area of increasing community interest is utilizing geophysical measurements to study processes at the Earth's surface. The SAGE facility will provide opportunities to study processes in the near-surface, such as hydrology, cryospheric processes, and glacier dynamics. (5) Education, Public Outreach, and Workforce Development: SAGE will develop a variety of educational resources and enable hundreds of undergraduate research opportunities. A major focus of the SAGE activities will be on broadening participation of underrepresented students through IRIS' new Urban Geosystems focus. Additionally, the facility will develop animations, simulations, and other visualizations of Earth processes to help instructors at all level teach about Earth Science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF PRINCETON UNIVERSITY, THEPrinceton UniversityJia Deng(734) 763-1560jiadeng@cs.princeton.edu09/19/2018$230,860$230,86009/01/201805/31/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITRI: Small: Inverse Rendering by Co-Evolutionary Learning1854435002484665002484665ROBUST INTELLIGENCEJie Yang(703) 292-4768jyang@nsf.govOff. of Research & Proj. Admin.PrincetonNJ08544-2020PrincetonUS12Princeton University35 Olden StreetPrincetonNJ08540-5233PrincetonUS12This project addresses the problem of inverse rendering: recovering 3D shape, material, and lighting from a single image. Inverse rendering is a fundamental problem in computer vision; it recovers the basic properties of a visual scene, and serves as a foundation for higher-level scene understanding such as recognizing objects, actions, and functionalities. Despite its fundamental importance, inverse rendering remains difficult. Solving inverse rendering can significantly advance computer vision and benefit a wide variety of applications from autonomous driving to assisting the visually impaired. This project develops new machine learning algorithms to advance the state of the art of inverse rendering. In addition, the project contributes to education and diversity by integrating research results into courses at various levels and by recruiting underrepresented groups to participate in this research.
This research advances inverse rendering technologies using computer graphics and machine learning. In particular, the research team develops two machine learning systems that co-evolve as adversaries: a rendering system that learns to compose 3D scenes and renders images using a graphics engine, and an inverse rendering system that learns to recover shape, material, and lighting from the rendered images. To develop the rendering system, the research team investigates new learning algorithms for adaptive, automatic scene composition. To develop the inverse rendering system, the research team investigates new learning algorithms that integrate neural networks and physics-based vision.VANDERBILT UNIVERSITY, THEVanderbilt UniversityDaniel B Work(615) 322-2697dan.work@vanderbilt.edu09/19/2018$57,603$57,60303/19/201812/31/2018GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: Synergy: Collaborative Research: Control of Vehicular Traffic Flow via Low Density Autonomous Vehicles1854321965717143004413456CYBER-PHYSICAL SYSTEMS (CPS)David Corman(703) 292-8950dcorman@nsf.govSponsored Programs AdministratioNashvilleTN37235-0002NashvilleUS05Vanderbilt UniversityTN37235-0002NashvilleUS05In the next few decades, autonomous vehicles will become an integral part of the traffic flow on highways. However, they will constitute only a small fraction of all vehicles on the road. This research develops technologies to employ autonomous vehicles already in the stream to improve traffic flow of human-controlled vehicles. The goal is to mitigate undesirable jamming, traffic waves, and to ultimately reduce the fuel consumption. Contemporary control of traffic flow, such as ramp metering and variable speed limits, is largely limited to local and highly aggregate approaches. This research represents a step towards global control of traffic using a few autonomous vehicles, and it provides the mathematical, computational, and engineering structure to address and employ these new connections. Even if autonomous vehicles can provide only a small percentage reduction in fuel consumption, this will have a tremendous economic and environmental impact due to the heavy dependence of the transportation system on non-renewable fuels. The project is highly collaborative and interdisciplinary, involving personnel from different disciplines in engineering and mathematics. It includes the training of PhD students and a postdoctoral researcher, and outreach activities to disseminate traffic research to the broader public.
This project develops new models, computational methods, software tools, and engineering solutions to employ autonomous vehicles to detect and mitigate traffic events that adversely affect fuel consumption and congestion. The approach is to combine the data measured by autonomous vehicles in the traffic flow, as well as other traffic data, with appropriate macroscopic traffic models to detect and predict congestion trends and events. Based on this information, the loop is closed by carefully following prescribed velocity controllers that are demonstrated to reduce congestion. These controllers require detection and response times that are beyond the limit of a human's ability. The choice of the best control strategy is determined via optimization approaches applied to the multiscale traffic model and suitable fuel consumption estimation. The communication between the autonomous vehicles, combined with the computational and control tasks on each individual vehicle, require a cyber-physical approach to the problem. This research considers new types of traffic models (micro-macro models, network approaches for higher-order models), new control algorithms for traffic flow regulation, and new sensing and control paradigms that are enabled by a small number of controllable systems available in a flow.JOHNS HOPKINS UNIVERSITY, THEJohns Hopkins UniversityYinzhi Cao(410) 516-6718ycao43@jhu.edu09/19/2018$449,005$465,00409/05/201808/31/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITTWC: Medium: Collaborative: Efficient Repair of Learning Systems via Machine Unlearning1854000001910777001910777Secure &Trustworthy CyberspaceDan Cosley(703) 292-8930dcosley@nsf.gov1101 E 33rd StBaltimoreMD21218-2686BaltimoreUS07Johns Hopkins University1101 E 33rd StBaltimoreMD21218-2686BaltimoreUS07Today individuals and organizations leverage machine learning systems to adjust room temperature, provide recommendations, detect malware, predict earthquakes, forecast weather, maneuver vehicles, and turn Big Data into insights. Unfortunately, these systems are prone to a variety of malicious attacks with potentially disastrous consequences. For example, an attacker might trick an Intrusion Detection System into ignoring the warning signs of a future attack by injecting carefully crafted samples into the training set for the machine learning model (i.e., "polluting" the model). This project is creating an approach to machine unlearning and the necessary algorithms, techniques, and systems to efficiently and effectively repair a learning system after it has been compromised. Machine unlearning provides a last resort against various attacks on learning systems, and is complementary to other existing defenses.
The key insight in machine unlearning is that most learning systems can be converted into a form that can be updated incrementally without costly retraining from scratch. For instance, several common learning techniques (e.g., naive Bayesian classifier) can be converted to the non-adaptive statistical query learning form, which depends only on a constant number of summations, each of which is a sum of some efficiently computable transformation of the training data samples. To repair a compromised learning system in this form, operators add or remove the affected training sample and re-compute the trained model by updating a constant number of summations. This approach yields huge speedup -- the asymptotic speedup over retraining is equal to the size of the training set. With unlearning, operators can efficiently correct a polluted learning system by removing the injected sample from the training set, strengthen an evaded learning system by adding evasive samples to the training set, and prevent system inference attacks by forgetting samples stolen by the attacker so that no future attacks can infer anything about the samples.UNIVERSITY CORPORATION FOR ATMOSPHERIC RESEARCHUniversity Corporation For Atmospheric ResAntonio J Busalacchi(303) 497-1652tonyb@ucar.edu09/19/2018$1$110/01/201809/30/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITThe Management and Operation of the National Center for Atmoshperic Research (NCAR)1852977078339587078339587NAT CENTER FOR ATMOSPHERIC RESSarah L. Ruth(703) 292-8521sruth@nsf.gov3090 Center Green DriveBoulderCO80301-2252BoulderUS02University Corporation For Atmospheric Res3090 Center Green DriveBoulderCO80301-2252BoulderUS02The National Center for Atmospheric Research (NCAR) is an NSF Federally Funded Research and Development Center. NCAR's mission is: to understand the behavior of the atmosphere and related Earth and geospace systems; to support, enhance, and extend the capabilities of the university community and the broader scientific community, nationally and internationally, and to foster the transfer of knowledge and technology for the betterment of life on Earth. NCAR fulfills this mission with tightly integrated programs organized around three overlapping primary areas of activity: cutting edge airborne and ground-based observational facilities, community weather, and climate models with many thousands of users, and petascale high-performance computing. These are accompanied by a broad portfolio of programs supporting education, career development, public engagement, and increasing diversity in the geosciences. This award funds the University Corporation for Atmospheric Research (UCAR) to manage and operate NCAR on behalf of NSF.
Understanding the Earth system is among the most exciting and important scientific challenges of our time - from the drivers of hazardous weather events that cost the nation tens of billions of dollars in damage each year to the longer-term impacts of climate change on the water cycle, water availability, and weather extremes. Under UCAR's management, NCAR will work with the broader scientific community to observe, understand, and ultimately predict the evolution of the atmosphere and related components of the Earth system at greater time and finer spatial scales. Ultimately, these advances will improve our nation?s ability to protect lives and property, enhance the American economy, and support national security.
Building upon its strong stewardship of NCAR since 1960, UCAR aims to ensure that NCAR continues to be a community leader and preeminent National Center that advances the atmospheric and Earth system science communities by conducting fundamental and transformative research at the frontiers of knowledge. UCAR will operate, maintain and develop NCAR's state-of-the-art observational, computational, and modeling facilities and services. UCAR will support NCAR by recruiting, developing, and retaining an expert and increasingly diverse workforce for the National Center. UCAR will also promote an ambitious and inclusive program of research, education, and outreach to serve the scientific community, and is moving aggressively to increase diversity and inclusiveness in its culture and in STEM education for the geosciences workforce. UCAR's vision includes identifying future requirements; developing compelling NCAR strategic plans; involving the community in planning, implementation and review; providing effective and efficient performance-based management of resources; making strategic investments in NCAR; creating an environment that attracts and retains exceptional talent; and enabling new partnerships that advance the science. UCAR brings a unique governance structure through its 117 members and many academic, government, and industry partners that will strengthen and promote NCAR to represent broad national and international interests.
Under this award, it is anticipated that NCAR will maintain a leadership role in creating objective information in support of national and international decisions on mitigation, adaptation, resiliency, and sustainability; and engaging interactively with the consumers of its science. This will result in improved prediction capabilities and more effective application of these advances to societal needs. Because UCAR's governance is based in academia, its management structure facilitates the development of future diverse scientists, provides access to world-leading facilities and exciting research opportunities for students, and engages the public through successful outreach program. UCAR's policy of free and open exchange of ideas, data, models, observational instruments and platforms, and information will maximize the impacts of the Center's research, development, and educational activities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.INCORPORATED RESEARCH INSTITUTIONS FOR SEISMOLOGYIncorporated Research Institutions for SeismologyRobert S Detrick(202) 682-2220detrick@iris.eduJohn Taber, Timothy K Ahern, Robert L Woodward09/19/2018$4,163,233$800,00009/01/201808/31/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth System Dynamics: Seismological Facility for the Advancement of Geoscience (SAGE) - OPP Scope1851037183277938183277938SAGEMargaret Benoit(703) 292-0000mbenoit@nsf.gov1200 New York Avenue, NWWashingtonDC20005-6142WashingtonUS00Incorporated Research InstitutionsDC20005-6142WashingtonUS00The IRIS (Incorporated Research Institutions for Seismology) Consortium will develop, operate, and maintain a distributed, multi-user facility entitled Seismological Facilities for the Advancement of Geoscience (SAGE). Expert professional staff, with guidance provided by the scientific community, will manage and operate a set of foundational capabilities that are essential for current research support, as well as frontier activities that will enable future research. The facility will promote advances in our understanding of Earth structure and dynamics, earthquakes and volcanic eruptions, and interactions between the solid Earth, hydrosphere, and atmosphere through management and operation of: 1) Global and regional continuously operating seismic networks, including the Global Seismographic Network; 2) Portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences. The seismological facilities provided through the SAGE contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; national security; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data and data products from SAGE will be used by state and federal agencies including the United States Geological Survey, National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, Department of Energy, and Department of Defense, for mission agency activities, including earthquake monitoring and characterization, tsunami warning, weather forecasting, water and environmental management, and nuclear test monitoring. SAGE programs will also support inquiry-based science education, enhancing students' abilities to engage directly with science and engineering principles and practice, and enabling them to pursue STEM careers in academia, industry, business, and government. The SAGE outreach activities promote public engagement and science literacy.
The SAGE facility provides instrumentation services; data services; and education, workforce development, and community engagement activities in support of seismology. Researchers use SAGE to gain valuable insights into fundamental Earth processes, and SAGE also provides key data for national security needs, including monitoring efforts of clandestine nuclear tests. The scientific priorities of the new facility would enable advances in the following areas: (1) Global Earth Structure and Dynamics: The facility would enhance our ability to resolve the three-dimensional structure of the Earth's interior and enable investigators to study processes that drive plate tectonics and natural hazards such as earthquakes, tsunamis, and volcanic eruptions. (2) Fault Zones and the Earthquake Cycle: Over the last decade, scientists have discovered a broad array of fault zone slip behaviors that span a wide variety of temporal and spatial scales. The SAGE facility will enable a variety of seismic and electromagnetic measurements to elucidate how these different types of behaviors start and stop, vary along fault zones, and interact with one another. (3) Magmas and Volatiles in the Crust and Mantle: Geophysical instrumentation is critical for understanding volcanic systems and minimizing risks associated with volcanic hazards. The capabilities provided by SAGE will enable researchers to study melt production, monitor its transport through the crust, and map out the plumbing systems of volcanoes. (4) Hydrosphere, Cryosphere, and Atmosphere: An area of increasing community interest is utilizing geophysical measurements to study processes at the Earth's surface. The SAGE facility will provide opportunities to study processes in the near-surface, such as hydrology, cryospheric processes, and glacier dynamics. (5) Education, Public Outreach, and Workforce Development: SAGE will develop a variety of educational resources and enable hundreds of undergraduate research opportunities. A major focus of the SAGE activities will be on broadening participation of underrepresented students through IRIS' new Urban Geosystems focus. Additionally, the facility will develop animations, simulations, and other visualizations of Earth processes to help instructors at all level teach about Earth Science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MATERIALS RESEARCH SOCIETYMaterials Research SocietyJohn J Lewandowski(216) 368-4234jjl3@case.eduJ. Ardie Butch Dillen09/19/2018$15,000$15,00011/01/201804/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSymposium: Advances in Intermetallic-Based Alloys for Structural & Functional Applications; 2018 Materials Research Society Fall Meeting; Boston, Massachusetts; 25-30 November 20181843435107328510Materials Eng. & ProcessingAlexis Lewis(703) 292-2624alewis@nsf.gov506 KEYSTONE DRWarrendalePA15086-7573WarrendaleUS12Materials Research Society506 Keystone DrWarrendalePA15086-7573WarrendaleUS12Intermetallic compounds are an integral part of materials design for structural and functional applications and understanding their behavior is critical to improved performance. Extensive research has been underway to understand the fundamental aspects of intermetallics and the knowledge base is continuously evolving. Nevertheless, significant knowledge gaps exist in the fundamental science of intermetallics, as well as in processing and scale-up for eventual application. This award supports a symposium on fundamental understanding of the processing, microstructure, and properties of these materials at the Materials Research Society (MRS) Fall Meeting in Boston, Massachusetts, November 25-29, 2018. This symposium series was started in 1984 and is one of the longest running symposia in MRS history.
This award will enable the attendance at the symposium of graduate students, post-doctoral researchers, early career faculty and researchers from underrepresented groups. Support for students and early career researchers for travel and registration at the MRS meeting is a critical part of broadening and educating the field of researchers, as well as advancing knowledge and information exchange about this important class of materials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.NORTHWESTERN UNIVERSITYNorthwestern UniversityHan Liu(412) 260-3224hanliu@northwestern.edu09/19/2018$237,718$237,71809/01/201712/31/2018GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITRI: Medium: Collaborative Research: Next-Generation Statistical Optimization Methods for Big Data Computing1840857160079455005436803ROBUST INTELLIGENCEWeng-keen Wong(703) 292-8930wwong@nsf.gov1801 Maple Ave.EvanstonIL60201-3149EvanstonUS09Northwestern University1801 Maple Ave.EvanstonIL60201-3149EvanstonUS09This project develops a new generation of optimization methods to address data mining and knowledge discovery challenges in large-scale scientific data analysis. The project is constructed in the context that modern computing architectures are enabling us to fit complex statistical models (Big Models) on large and complex datasets (Big Data). However, despite significant progress in each subfield of Big Data, Big Model, and modern computing architecture, we are still lacking powerful optimization techniques to effectively integrate these key components.
One important bottleneck is that many general-purpose optimization methods are not specifically designed for statistical learning problems. Even some of them are tailored to utilize specific problem structures, they have not actually incorporated sophisticated statistical thinking into algorithm design and analysis. To tackle this bottleneck, the project extends traditional theory to open new possibilities for nontraditional optimization problems, such as nonconvex and infinite-dimensional examples. The project develops deeper theoretical understanding of several challenging issues in optimization (such as nonconvexity), develops new algorithms that will lead to better practical methods in the big data era, and demonstrates the new methods on challenging bio-informatics problems.
The project is closely related to NSF's mission to promote Big Data research, and will have broad impacts. In the Big Data era, we see an urgent need for powerful optimization methods to handle the increasing complexity of modern datasets. However, we still lack adequate methods, theory, and computational techniques. By simultaneously addressing these aspects, this project will deliver novel and useful statistical optimization methods that benefit all relevant scientific areas. The project will deliver easy-to-use software packages which directly help scientists to explore and analyze complex datasets. Both PIs will also design and develop new classes to teach modern techniques in handling big data optimization problems. All the course materials - including lecture notes, problem sets, source code, solutions and working examples - will be freely accessed online. Moreover, both PIs will write tutorial papers and disseminate the results of this research through the internet, academic conferences, workshops, and journals. Through senior theses and potentially the REU (Research Experiences for Undergraduates) program, the proposed project will also actively include undergraduates and engage under-represented minority groups.
To achieve these goals, this project develops (i) a new research area named statistical optimization, which incorporates sophisticated statistical thinking into modern optimization, and will effectively bridge machine learning, statistics, optimization, and stochastic analysis; (ii) new theoretical frameworks and computational methods for nonconvex and infinite-dimensional optimization, which will motivate effective optimization methods with theoretical guarantees that are applicable to a wide variety of prominent statistical models; (iii) new scalable optimization methods, which aim at fully harnessing the horsepower of modern large-scale distributed computing infrastructure. The project will shed new theoretical light on large-scale optimization, advance practice through novel algorithms and software, and demonstrate the methods on challenging bio-informatics problems.UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE, THEUniversity of North Carolina at CharlotteValentina Cecchi(704) 687-8730vcecchi@uncc.eduZachary J Wartell, Tao Hong, Isaac Cho09/19/2018$299,237$299,23710/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Visual Analytics for Enhanced Decision-Making and Situational Awareness in Modern Distribution Systems, with a Focus on Outage Prediction and Management1839812066300096142363428ENERGY,POWER,ADAPTIVE SYSAnil Pahwa(703) 292-2285apahwa@nsf.gov9201 University City BoulevardCHARLOTTENC28223-0001CharlotteUS12University of North Carolina at CharlotteNC28223-0001CharlotteUS12This project addresses the need to develop a fully visible, controllable, and resilient electric power distribution system. Although the distribution system accounts for over 75% of the outages in the power grid, power system operators currently have limited situational awareness at the distribution level, limited visibility beyond the substations, limited information on the network and its connectivity. With the rapid increase in amount and type of data accumulated in the distribution system, i.e. from Advanced Metering Infrastructure (AMI) and remotely monitored and controlled devices, the need to glean actionable intelligence from it is of paramount importance. Integrating data from these heterogeneous datasets (Geographical Information System (GIS), Supervisory Control and Data Acquisition (SCADA), AMI, Outage and Distribution Management Systems (OMS/DMS)) is a first step towards achieving this. The goal of this project is to develop a visual analytics platform to leverage the integrated dataset, enabling distribution system operators to visualize and analyze the state of the distribution system over time, empowering them to identify categorical patterns of events in space and time via highly coordinated visualizations. The project comprises three main components: 1. A data-driven approach to uncover useful information from streaming and historical data, strengthened by 2. Situationally-aware modeling and simulation of the electric power distribution system, and 3. A visual analytics system, leading to prescriptive analytics, actionable knowledge for the indispensable human in-the-loop. The developed infrastructure would enable and enhance real-time fast and confident decision-making, thus supporting overall efficiency and reliability improvements in the electric power distribution system, reducing current outage times and improving reliability indices. Benefits would accrue in terms of savings as well as in terms of customer satisfaction. The principal investigator of this project is the founder and faculty advisor of the local student chapter of IEEE Women in Engineering (WIE) and she plans to leverage that connection to broaden participation in this project.
For complete situational awareness leading to decision-making, there needs to be powerful, automated analytics, enhanced by a deep understanding of the physical system, but it is also essential that the human be placed in the loop at the right place and time. For this reason, three components are integrated: 1. Data-driven real-time probabilistic outage prediction, coupled with 2. Situationally-aware modeling and simulation of the distribution system, and with 3. An interactive visual analytics system to provide visual and exploratory analytics. Utilizing real-time data streams coming from the distribution system (SCADA, AMI, Digital Fault Recorders) and from weather stations, together with historical data, advanced real-time data analytics algorithms are applied to strategically process the data, obtaining, for example, accurate loading conditions and developing probabilistic outage predictions. This sensed and processed information is then utilized, as needed, by the now situationally-aware distribution system electrical model to perform simulations. The simulations in turn provide input feedback to probabilistic scenarios and define system constraints for the analytics modules. Since human-in-the-loop is important, these analytics are closely coupled to the representations and modes of interaction in the interactive visual analytics system so that the right information is presented to the user at the right time. Thus, the developed framework results in a hybrid approach that leverages data-driven methodologies, the physical system, and visual analytics, to provide much improved decision-making capabilities. This project investigates the science of real-time learning and decision-making, while also looking closely at the technology for data-driven distribution system analysis coupled with deep understanding of the physical system. The project will provide theoretical underpinnings and novel methods to significantly move distribution modernization efforts forward, including improvements in system reliability and resiliency, new modes for management, new paradigms and paths for customer-utility cooperation, and a new approach to handling big data in the electric grid.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ARIZONA STATE UNIVERSITYArizona State UniversityMaria N LasalaBlanco(480) 965-4225Maria.Lasala.Blanco@asu.edu09/19/2018$6,923$6,92307/01/201807/31/2018GrantNSF4900490047.075040100 NSF RESEARCH & RELATED ACTIVITRefugee and European Cities Panel1838616943360412806345658POLITICAL SCIENCEBrian D. Humes(703) 292-7284bhumes@nsf.govORSPATEMPEAZ85281-6011TempeUS09Arizona State UniversityPO Box 876011TempeAZ85281-6011TempeUS09General Abstract
This proposal studies how advanced democracies help or hinder the integration of immigrants. It seeks to identify when, how, and under what circumstances individual immigrants acquire positive attitudes toward democratic values, institutions, and toward the receiving country. This is a topic of great importance, as it is clear that not all immigrants adopt pro-democratic values, as evident by instances of hostility on the part of immigrants directed at the receiving country. The project will study refugees in order to assess their attitudes toward the host country upon their arrival, and then subsequently track the respondents' attitudes over time. With an increasing number of individuals seeking to flee their home countries to move to advanced democracies, the topic is timely and important. By assessing how immigrants acquire (or fail to acquire) pro-democracy attitudes, the research is poised to help determine strategies to help integrate the new arrivals into democratic society. Successful programs that foster integration can help to reduce the negative consequences often associated with large influxes of refugees. Those findings would be of great values to both the scholarly and policymaking communities.
Technical Abstract
This proposal studies how, when, and why some immigrants successfully integrate into democratic societies, while others do not. The research design allows for the investigators to evaluate the immigrant respondents' attitudes toward democracy upon arriving in the receiving country, and subsequently at multiple points over time. Unlike previous studies, the team is able to study refugees fleeing a specific country, but who ultimately end up dispersed across multiple advanced democratic countries. This will allow the team to assess how different conditions across countries may contribute to the successful integration of immigrants and the adoption of pro-democratic values by these immigrants. To do so, the team will utilize state-of-the-art cellular technology, an experimental research design, and a panel data survey design to assess the success or failure of host states to integrate newly arrived immigrants. By identifying factors that contribute to successful integration efforts that foster democratic values among newly arrived immigrants, this research will provide valuable insights to scholars who study civic values and political socialization. Likewise, the findings will be of great importance for policymakers who must design appropriate and effective integration programs and policies for particular immigrants to their country.COLLEGE OF OUR LADY OF THE ELMS INCCollege of Our Lady of the ElmsBeryl Hoffman(413) 594-2761hoffmanb@elms.edu09/19/2018$38,709$38,70910/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Broadening Participation and Building Pathways in Computer Science (CS) through Concurrent Enrollment1837112087444584STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.gov291 Springfield StreetChicopeeMA01013-2837ChicopeeUS01College of Our Lady of the Elms291 Springfield StreetChicopeeMA01013-2837ChicopeeUS01This project studies the implementation and outcomes of Concurrent Enrollment (CE) programs as a vehicle for broadening participation in high school to college pathways in Computer Science (CS). The Mobile Computer Science Principles (Mobile CSP) project at the College of St. Scholastica, an established curriculum endorsed by the College Board for its alignment with the Advanced Placement (AP) CSP framework, has formed a Research-Practitioner Partnership (RPP) with CE programs at Capital Community College in Hartford, Connecticut and Southwest Minnesota State University in Minnesota and with partner school districts in each state.
The RPP project explores whether CS through CE can broaden the high school to college pathway in computing disciplines for those traditionally underrepresented in these fields--female, underrepresented minority, and low-SES students. While the AP CSP course has enrolled a more diverse group of students than previous AP CS courses, it is not as diverse as other AP courses. CE programs appear to have better penetration than AP among schools that predominantly serve underrepresented minorities and low-SES students, showing promise for broadening participation in other disciplines and encouraging college matriculation.
By implementing and studying CS through CE in two different contexts (rural and low-SES in Minnesota and urban, diverse, and low-SES in Connecticut), the project contributes to transforming the educational pathways in CS in a variety of contexts and to understanding the supports and barriers to implementing CSP as CE with a broadening-participation goal. This project provides professional development and support of 40 high school teachers to teach a CE version of the Mobile CSP course among partnering school districts over the course of 3 years. The goals of this RPP project are (1) to examine and address the supports and barriers to implementing and sustaining Mobile CSP as a concurrent enrollment course and (2) to study whether a CE implementation of the CSP course broadens participation in computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RURISOND, INCRurisond, Incrobert s stevenson(650) 395-7136rstevenson@rurisond.com09/19/2018$745,388$745,38809/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Long Range 2-way Communications for the Remote IOT1831259080294715SMALL BUSINESS PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov2725 Ohio AvenueRedwood CityCA94061-3237Redwood CityUS18Rurisond, Inc1155 Broadway, Suite 100Redwood CityCA94063-3121Redwood CityUS14The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will allow highly cost effective, 2-way communications to be delivered to machinery and 'Things' over extremely long and non-line-of-sight distances using underutilized frequencies and new hardware and software techniques. The resulting technologies will provide 2-way connectivity where cellular does not exist and where other techniques (Satellite) are too expensive. This will result in near universal availability of the Internet-of-Things at costs superior to legacy approaches and which are appropriate for applications typically seen in Internet-of-Things applications. Further, the work will have broad impact in allowing more balanced utilization of the radio spectrum which cannot be addressed (either economically or at all) with legacy wireless techniques.
The proposed project will create a new system of hardware, software, frequency and operating techniques which will allow underutilized spectrum to be used to deliver 2-way communications to very remote machines and things. The work will build on our Phase I accomplishments to create production-ready designs of two new wireless systems, signal processing software to allow use of challenging spectrum while avoiding existing users, create the first instance of a cloud based infrastructure for automated control and coordination of our architecture, and, the creation of a basic set of deployment tools and techniques to support field operations. We expect to continue building a significant base of Intellectual Property as we pursue the work.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MARYLANDUniversity of Maryland College ParkThomas E Murphy(301) 405-0030tem@umd.eduEdo Waks, Marina S Leite, Kevin M Daniels09/19/2018$606,237$606,23709/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Development of Ultrafast Near-Field Scanning Optical Microscope1828155790934285003256088MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.gov3112 LEE BLDG 7809 Regents DriveCOLLEGE PARKMD20742-5141College ParkUS05University of Maryland College ParkBldg. 223, 8279 Paint Branch Dr.College ParkMD20742-3511College ParkUS05Many phenomena in natural and engineered systems are both spatial and temporal, meaning that they involve dynamical changes and movements of nonuniform patterns. Examples include wave propagation, heating and cooling, chemical reactions, and diffusion. The ability to visualize these phenomena is fundamentally limited both by how fast they are and how small they are. Science has made remarkable improvements in the spatial resolution of microscopes, which has enabled the now-mature field of nanotechnology. At the same time, pulsed laser systems can resolve dynamical processes with femtosecond resolution -- far faster than even the best electrical detectors or cameras. This project aims to develop a novel instrument that will combine the spatial capabilities of a near-field microscope with the temporal resolution of a femtosecond laser, which is currently not available in commercial instruments. This tool will be capable of resolving nanoscale spatial structure, while simultaneously measuring ultrafast effects with femtosecond resolution in systems ranging from nanoelectronic devices to metallic nanostructures and solar cells. The unique instrument will provide valuable training for scientists and students at all levels, who will both develop and utilize it.
The combination of two different technologies, the femtosecond laser and the near-field microscope, will require significant engineering research, iteration, optimization, and system integration over the three-year period of this project. The proposed instrument will replace the continuous-wave laser typically used in a near-field scanning optical microscope with an ultrafast tunable pulsed laser, in order to produce an intense spatially and temporally localized optical stimulus that can excite nonlinear effects in the material or device at the nanoscale. A second, weaker temporally-delayed optical pulse will then be used to probe the properties and dynamics with femtosecond resolution. The proposed system will allow for time-resolved and spatially-resolved measurements at wavelengths ranging from 340 nm to 12,000 nm. The new instrument will enable the study of hot-carrier dynamics in metals and two-dimensional (2D) materials, investigation of the dynamic electrical response of perovskite materials for advanced optoelectronics, direct imaging of nanophotonic devices and resonant structures, and observation of heterogeneous surface chemistry and grain boundaries in transition-metal oxides.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.LEHIGH UNIVERSITYLehigh UniversityChengshan Xiao(610) 758-4069xiaoc@lehigh.edu09/19/2018$200,000$200,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Hybrid Precoding for Massive MIMO Communication Networks1827592808264444068570936COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govAlumni Building 27BethlehemPA18015-3005BethlehemUS15Lehigh University19 Memorial Drive WestBethlehemPA18015-3084BethlehemUS15EAGER: Hybrid Precoding for Massive Multiple-Input Multiple-Output Millimeter Wave Wireless Communication Networks
Future smart and connected communities will place tremendous demand on wireless communications due to the ever-growing popularity of smartphones, autonomous vehicles, and mobile devices. The massive Multiple-Input Multiple-Output (MIMO) technology, in combination with millimeter wave (mmWave) spectrum utilization, is considered as a key breakthrough for enabling enormous data-rate increase for next generation wireless networks. In massive MIMO systems, a very large number of antennas is employed at the base station to communicate many mobile users simultaneously. However, this large number of antennas can lead to prohibitive cost and power consumption if conventional approach which requires one radio frequency (RF) chain per antenna is adopted. This project focuses on novel hybrid precoding designs which will not only reduce the number of RF chains but also maximize the data rate. The hybrid precoding consists of analog and digital precoders, where the digital precoder is realized by a small amount of RF chains, and the analog precoder is realized by phase shifters. Therefore, the cost, complexity and power consumption of massive MIMO systems can be reduced dramatically. The proposed research can have a large impact on the design and development of future generation of wireless networks, for which massive MIMO and mmWave are key enabling technologies. The research results will be integrated into the classes for electrical engineering and computer engineering majors through designing new course projects. Research findings will be broadly disseminated through conference presentations and journal publications. Moreover, the project will help increase participation of under-represented minorities and enhance outreach activities to attract female students to careers in engineering.
This project aims to investigate hybrid precoding design methods that can drastically reduce the cost, complexity and power consumption while approaching the optimal performance of fully-connected, unconstrained massive MIMO systems. The project formulates the hybrid precoding design of multi-user massive MIMO systems into a joint optimization of analog and digital precoders with dynamic resource allocation which includes subarray selection, power allocation, and modulation-coding-rate selection. The joint optimization will enable the hybrid system with a significantly reduced number of RF chains to achieve similar performance of fully-connected massive MIMO systems at a fractional cost. The dynamic resource allocation will help to achieve best throughput for given channel conditions. Furthermore, the proposed approach utilizes finite-alphabet inputs and statistical channel state information (CSI) instead of the idealistic Gaussian inputs and instantaneous CSI, thus improving the robustness of the optimized precoders for practical systems. The objective of this project is expected to be accomplished by three specific tasks. First, theoretical studies of the achievable data rates will address the fundamental tradeoff between performance and cost of hybrid precoding. Second, algorithm research will derive low-complexity solutions to solve the NP-hard optimization problems. Third, machine learning techniques will be applied to learn the features and transition probabilities of the Markov decision processes governing the online resource allocation and hybrid precoding.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF COLORADO, THEUniversity of Colorado at BoulderRobert R McLeod(303) 735-0997mcleod@colorado.eduStephanie J Bryant, Virginia L Ferguson, Michael C Cole09/19/2018$399,199$399,19910/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITGOALI: Projection Stereolithography of Gradient Viscoelastic Polymer Nanocomposites1826454007431505007431505Manufacturing Machines & EquipBrigid Mullany(703) 292-8360bmullany@nsf.gov3100 Marine Street, Room 481BoulderCO80303-1058BoulderUS02University of Colorado at BoulderBoulderCO80303-1058BoulderUS02Polymer reinforced composites are materials that combine reinforcement materials such as carbon or glass fiber, or glass particles with a polymeric base material to produce a material with enhanced mechanical properties. Utilization of these materials has revolutionized industries involved in aerospace, automotive, and sporting goods manufacture. Increasingly, industry is turning to additive manufacturing, or 3D printing, to realize customized components with complex geometries. However, stereolithography, an additive manufacturing process that uses light to locally cure (harden) a liquid polymer resin in layers to build up a solid part, cannot successfully produce polymeric reinforced composites. Nor can the process easily incorporate material property gradients within a single build. This Grant Opportunities for Academic Liaison with Industry (GOALI) project seeks to overcome these limitations by understanding the material processing interactions occurring during a modified stereolithography printing process capable of combining polymers and nanoparticles to produce printed polymer composite materials. Success will advance the performance and range of polymeric materials that can be printed via stereolithography, and in doing so will realize the 3D printing of high performance, customizable, functionally graded components. This has the potential to advance the competitiveness of core US industries involved in the manufacture of aerospace, automotive, and medical components. As Align Technology, a manufacturer utilizing stereolithography in their custom-made orthodontics fabrication process, is a collaborator on this project the students involved in the project will not only be exposed to advanced material science and manufacturing technologies but will also gain an understanding of industrial challenges and drivers. Extended online courses will be made available to students and practicing engineers, providing flexible learning opportunities to keep informed of new developments in materials science and manufacturing.
The primary goal of this project is to elucidate the structure/property relationships of gradient composite polymers printed by gray scale stereolithography of a matrix polymer followed by swelling with a reactive filler containing nanoparticles. A secondary goal is to reduce, control or eliminate the large internal stresses caused by polymerization shrinkage and solvent swelling of stereolithographic parts. The latter will be achieved by employing covalent adaptable matrices, e.g. addition-fragmentation chain transfer backbones that rearrange to relax stress in the presence of radicals. To achieve these goals the following tasks will be conducted; 1) precise, macroscopic characterization of matrix monomer-to-polymer conversion as a function of processing conditions and how this partial conversion controls swelling of the filler, 2) validation of the macroscopic predictions on the micron scale via gray-scale stereolithography of the matrix followed by swelling and polymerization of the filler, 3) validation of the predicted viscoelastic behavior of inhomogeneous printed nanocomposites, and 4) demonstration that reversible addition-fragmentation chain transfer chemistry can be leveraged to provide local stress control in bulk composites. If successful the knowledge gained will be used to print and verify the predicted properties of a printed trinary nanocomposite with photo-induced plasticity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF THE COLORADO SCHOOL OF MINESColorado School of MinesColin A Wolden(303) 273-3544cwolden@mines.edu09/19/2018$371,192$371,19209/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITContinuous Manufacturing of Anhydrous Metal Sulfide Nanocrystals1825470010628170010628170NANOMANUFACTURINGKhershed Cooper(703) 292-7017khcooper@nsf.gov1500 IllinoisGoldenCO80401-1887GoldenUS07Colorado School of MinesGoldenCO80401-1887GoldenUS07Metal sulfide nanocrystals have attracted great attention because of their excellent properties and widespread applications in diverse fields including lubrication, optoelectronics, catalysis, biotechnology, and energy storage. Reactive precipitation of nanocrystals is typically accomplished by combining aqueous solutions to create supersaturated mixtures. Such processes are sensitive to processing conditions making the synthesis of anhydrous phase pure materials challenging, in general, and impossible for moisture sensitive alloys. This award supports the study of the manufacture of anhydrous metal sulfide nanoparticles through the reaction of hydrogen sulfide gas with metal-organic precursors in an organic solution. The project addresses the engineering challenges involved in translating this solution-based approach into a scalable nanomanufacturing process. It develops a bubble column reactor platform for continuous manufacturing of the nanocrystals via reactive precipitation. The project targets important materials challenges facing next generation battery technologies. Such a manufacturing capability is critical for enabling widespread deployment of renewable wind- and solar-generated electricity, which greatly impacts the nation's prosperity and infrastructure. This project provides interdisciplinary training for undergraduate and graduate engineers and scientists in energy technology areas. Project results are integrated into the undergraduate curriculum. The building and implementation of the bubble-column platform serves as a module in a unit operations laboratory course.
This project advances a green chemistry approach that results in complete reduction of the hazardous industrial waste gas hydrogen sulfide while generating metal sulfide nanocrystals and recovering valuable hydrogen. The project aims to extract general principles for the design and operation of reactive precipitation processes in bubble columns, including a four-phase design. The research involves demonstrating the ability to control the size and morphology of metal sulfide nanoparticles through rational selection of chemistry (solvent, auxiliary reagent) and systematic manipulation of mass transport parameters. Studies of nanoparticle synthesis under semi-batch operation are used to guide the design and implementation of a continuous manufacturing platform. The structure, properties and performance of the nanoparticles are characterized through the fabrication and evaluation of prototype cathodes and solid-state electrolytes. Continuous production is expected to improve control over nanocrystal shape and size distribution that is critical in the applications of these materials. The combination of gas-phase reactants with organic solutions offers a new paradigm for the reactive precipitation of moisture sensitive nanoparticles.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VANDERBILT UNIVERSITY, THEVanderbilt UniversityNoel Enyedy(310) 206-6271enyedy@gseis.ucla.edu09/19/2018$307,177$307,17606/16/201808/31/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITDIP: Collaborative Research: Interactive Science Through Technology Enhanced Play (iSTEP)1855048965717143004413456Cyberlearn & Future Learn TechTatiana D. Korelsky(703) 292-8930tkorelsk@nsf.govSponsored Programs AdministratioNashvilleTN37235-0002NashvilleUS05VanderbiltPMB 407749 2301 Vanderbilt PlaceNashvilleTN37235-0002NashvilleUS05The iSTEP project addresses a basic research question by exploring the role of the body and physical activity in learning through the design of a new genre of developmentally appropriate learning technologies for young children. There is increasing recognition that the body plays a role in cognition: human beings, especially young children, understand complex concepts in part by relating them to how we move our own bodies. In extending these ideas, the iSTEP project also aims to develop teaching techniques and technological tools that can be used in real classrooms in the near future. Instead of supporting the learning of individual students as many current technological advances attempt to do, the iSTEP project creates opportunities for entire classrooms of students to engage together to model scientific phenomena using their bodies. For instance, a classroom of students can use their own bodies to model how a state of matter such as liquid is made up of many moving particles and technologically enhance this activity to improve learning. The iSTEP project builds upon the already successful STEP mixed reality platform (IIS-1323767) by adding new forms of interaction - the use of gestures and physical props to control the STEP computer simulation. Adding these new forms of interaction allows us to examine their role in supporting learning.
The existing open source STEP platform uses commercially available vision-based sensors to track the motion of up to 12 children in an 8m x 8m space. The children simply walk into the space, are assigned an avatar (i.e., they become a water particle), and that avatar follows them as they move around the room. The children's avatars are then immersed in a virtual simulation that is programed to mimic the scientific concept they are learning. In this case, the state of matter of water (e.g., solid, liquid, or gas) is determined by how fast the children move and the relative distance between them. This allows the students to discover the laws that govern state changes through their collaborative activity. Students can also use the PLAE interface (IIS-1522945) to annotate the simulation and create representations of their peers' activity, helping them all to reflect on the underlying principles inherent in the system. In iSTEP, students will now also be able to control the simulation by gesturing, posing with their whole body, and by manipulating physical objects in addition to the previous model of interacting with their entire body. In addition, by using smart watches, the project will explore alternative forms of feedback to the students as they can feel vibrations, hear sounds, and even see simple images that are targeted to help them explore the simulation. In the first round of experiments this project will contrast the gesture (and pose) interface with a new interface that uses physical props to see how each contributes to student learning. In the final year, these will be integrated to develop deeper insights into how they can best be used to support the design of learning environments that build on mixed reality systems.JOHNS HOPKINS UNIVERSITY, THEJohns Hopkins UniversityYinzhi Cao(410) 516-6718ycao43@jhu.edu09/19/2018$500,000$500,00008/31/201808/31/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSaTC: CORE: Small: Preventing Web Side-channel Attacks via Atomic Determinism1854001001910777001910777Secure &Trustworthy CyberspaceSol J. Greenspan(703) 292-8910sgreensp@nsf.gov1101 E 33rd StBaltimoreMD21218-2686BaltimoreUS07Johns Hopkins UniversityMD21218-2686BaltimoreUS07Web browsers are vulnerable to side-channel attacks, which usually play an important, first-step role in jump-starting a chain of attacks. For example, a web-level precise clock can help adversaries to break operating system level memory protection mechanisms, such as address-space layout randomization (ASLR). Browser fingerprinting, a variation of web side channels, can be used to obtain users' private information for launching social engineering attacks. In addition, web side-channel attacks alone can also reveal private information, such as illnesses and medications of patients and the number of social network users' friends. The project is to design, implement and evaluate a novel defense architecture integrating atomic determinism, a brand-new concept of determinism tailored-made for web browsers, to provably prevent web side-channel attacks, thus protecting web users' security and privacy.
The key insight of atomic determinism is that a web browser can be considered as a composition of several atomic units, called reference frames (RFs), an abstract concept borrowed from physics. The atomic determinism of web browsers defines that each RF contains only one clock and at most one observer, e.g., a Turing-complete program controlled by the adversary. From the viewpoint of the observer, the clock in the RF ticks deterministically, i.e., being the same in every runtime; by contrast, from the viewpoint of an oracle, e.g., a user of the browser, the clock in the RF ticks normally without performance slowdown. The project adopts two tactics to incorporate atomic determinism into web browsers, i.e., designing a browser add-on and modifying a modern web browser. The former, which translates existing programs and overwrites existing function definitions, facilitates the general web users in short-term; the latter, which fundamentally changes the browser architecture, facilitates users with special needs and can be integrated into a mainstream browser in a longer term. The greatest impact of this project is novel, effective approaches, systems, and technologies to improving the security and privacy of browsers, benefiting web users from both the academia and the general public. The principal investigator (PI) also involves undergraduates, women, K-12 students and minorities in the project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.NORTHWESTERN UNIVERSITYNorthwestern UniversityTeri W Odom(847) 491-7674todom@northwestern.eduGeorge C Schatz, Bozhi Tian09/19/2018$999,999$999,99909/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITConvergence: RAISE: Auto-regulatory Scaffolds for Directed Evolution of Non-living Functional Materials1848613160079455005436803AM-Advanced ManufacturingKhershed Cooper(703) 292-7017khcooper@nsf.gov1801 Maple Ave.EvanstonIL60201-3149EvanstonUS09Northwestern University2145 Sheridan RoadEvanstonIL60208-3113EvanstonUS09This award supports a new approach to identify and realize new functional materials under realistic conditions. The method is directed evolution of non-living materials based on auto-regulatory scaffold hosts. The method is bio-inspired. It mimics the approach observed in living things. The research involves developing a platform which incorporates synthesis, screening and feedback, by design, and offers a practical pathway to materials discovery. This strategy overcomes the limitations of screening materials via computer simulations only. The project builds on the convergence of different research areas such as tissue engineering, systems biology, scalable nanomanufacturing and machine learning. The discovery of new materials leads to new functionalities, which leads to new devices and systems, which leads to new products, which benefits society and economy and enhances the nation's prosperity and security. The project demonstrates a paradigm shift in materials discovery and invention. Education plans involve training graduate students and postdocs in convergence approaches to materials screening and discovery, design and realization of auto-regulatory scaffolds and machine learning. Outreach plans are to develop programs such as dissemination through public lectures, integration of research results into new undergraduate courses, and publication of perspectives that combine convergence of research from different fields.
The project's approach is to screen materials through the auto-regulatory interaction of sensors, regulators and known and unknown materials. These components are located on scaffolds, which are tissue engineering-inspired constructs, whose dimensions are convenient for the developed fabrication and synthesis tools and which may be adapted to a wide range of node materials that include hydrogels, polymers, nanomaterials, and biomaterials. The auto-regulatory aspects of the research involve humidity and photothermal energy sources, among others. The auto-regulatory processes are based on interference effects, thermal expansion, chemical reactions, and cellular response and motion for which the project develops theory and modeling. One benefit of the evolutionary platform is that it interfaces seamlessly with seemingly incompatible combinations of materials such as hydrogels and semiconducting nanomaterials or biological cells and inorganic materials. Materials screening is coupled with machine learning methods for prediction of new materials, which can be extended to other user-defined outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.COLORADO SEMINARYUniversity of DenverMichael Campbell(949) 233-9352campbellmi@umsl.edu09/19/2018$174,913$174,91309/15/201808/31/2020GrantNSF4900490047.075040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: State Variation in Mass Incarceration Reforms1840914007431760007431760LAW AND SOCIAL SCIENCESBrian Bornstein(703) 292-5366bbornste@nsf.gov2199 S. University Blvd.DenverCO80210-4711DenverUS01University of DenverdenverCO80210-4711DenverUS01After years of increasing incarceration in the United States, recently many states have passed reforms aimed at reducing their prison populations. However, not all states have embraced reform of their incarceration rates and policies. This project will examine what has led some states but not others to initiate new policies that could reduce rates of imprisonment. Consequently, this project takes advantage of the shift in national context and the new variation in state level reforms to assess how states create or impede significant reforms of their incarceration policies.
The project will examine legislative incarceration reform efforts in several states between 2000 and 2016. To do so, the project will use a paired case study comparison design. Three sets of state-pairs in different geographical regions will be matched on theoretically relevant variables known to correlate with penal policy and incarceration rates. The matched state-pairs design allows for variation in extent of reform. Data for the project will include archival and legislative documents, media content, and interviews. De-identified data from the project will be made publicly available. In this way, the project will help determine why some states have enacted incarceration reform, while others have been impeded in doing so. The project also will help identify effective strategies, resources, and processes with the most potential to better understand unnecessary incarceration within different state contexts.UNIVERSITY OF TENNESSEEUniversity of Tennessee KnoxvilleYilu Liu(855) 974-4129liu@utk.eduLin Zhu09/19/2018$275,762$275,76209/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Intelligent Mitigation of Low-Frequency Oscillations in Smart Grid Using Real-time Learning1839684003387891003387891ENERGY,POWER,ADAPTIVE SYSAnil Pahwa(703) 292-2285apahwa@nsf.gov1 CIRCLE PARKKNOXVILLETN37996-0003KnoxvilleUS02University of Tennessee Knoxville1 Circle ParkKnovxilleTN37996-0003KnoxvilleUS02As a critical underpinning of modern society, the electric power grid is one of the most complex and man-made dynamic systems in the world. Numerous real-time data of different types, different components, and various locations are generated to monitor and control power grids. Currently, the control of large-scale power grids is still mainly based on the physical system model, while the hidden knowledge in the abovementioned large-volume data has not been fully exploited. This project selects one typical control function in smart grids, low-frequency oscillation control, to explore the potential to enhance smart grid controls using the hidden knowledge.
Low-frequency oscillation is a common phenomenon in operation of large-scale power systems. If not controlled properly, these oscillations may degrade power system security and make a large number of customers lose their power. This project aims at developing an intelligent controller to mitigate these low-frequency oscillations using data and machine learning technologies. If successful, it will advance the technology in smart grid, and remove obstacles for application of machine learning technologies in smart grid control. The proposed approach will contribute to more secure, reliable and economic operations of U.S. power grids. For example, the risk of blackout can be significantly mitigated; and thus outage cost could be saved, e.g., more than $1 billion for U.S. western grid collapse in 1996. The proposed project is also coupled with a broad dissemination of research findings and a strong educational component to engage students from underrepresented groups.
The proposed research effort focuses on a completely new design methodology of intelligent oscillation damping control using the data-driven models. These data-driven models of power grids derive from synchronized measurement data using machine learning technologies, in conjunction with power grid domain knowledge. Specifically, this project will: (1) build a self-evolving dynamic knowledge base based on historical measurement data under different oscillation scenarios; (2) extract the critical features from historical and real-time data, and select the optimal features to improve data-driven model prediction accuracy; (3) develop machine learning algorithms to predict data-driven models for oscillation damping control design; and (4) validate and demonstrate the proposed methodology via computer simulations and hardware testbed experiments. This advanced approach will contribute to the energy security and efficiency of the U.S. electric power grids. This project will expose both undergraduate and graduate students to the state-of-the-art machine learning education and workforce training program. By coordinating with an established outreach program in an existing NSF/DOE engineering research center, the research results will be integrated into weekly seminars and short courses that are accessible to four partner universities, nine affiliate universities and more than 35 industry partners. Moreover, this project will encourage students to get involved with STEM (Science, Technology, Engineering and Mathematics) courses early in their pre-college years to prepare for STEM careers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TEXAS A&M ENGINEERING EXPERIMENT STATIONTexas A&M Engineering Experiment StationLe Xie(979) 845-7563le.xie@tamu.eduDileep Kalathil09/19/2018$248,799$248,79910/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Precision Reserves from Flexible Loads: An Online Reinforcement Learning Approach1839616847205572847205572ENERGY,POWER,ADAPTIVE SYSAnthony Kuh(703) 292-2210akuh@nsf.govTEES State Headquarters Bldg.College StationTX77845-4645College StationUS17Texas A&M Engineering Experiment Station3128 tamuCollege StationTX77843-3128College StationUS17This proposal explores an online reinforcement learning framework that can provide high capacity rating and scheduling of many end user-level flexible resources such as swimming pools. In sharp contrast with conventional approaches of statically and uniformly treating end user loads with small capacity rating and scheduling them via heuristics based algorithms, the proposed framework will provide a theoretically rigorous and practically scalable approach for learning the unknown parameters of end user loads and adaptively controlling them with provable guarantees.
Intellectual Merit:
(i) This proposal will illustrate the possibility of substantial increasing of capacity credit from end user demand response in provision of spinning reserves via scalable real-time estimation and control as opposed to the conventional heuristic based scheduling algorithms. (ii) This proposal will introduce a learning and adaptive control algorithm using the framework of online reinforcement learning to address the operational problems when the consumer specific parameters are unknown. (iii) This proposal will introduce an index-based learning and scheduling algorithm that scales only linearly with the number of end users. (iv) This proposal will test a data-driven optimal scheduling that jointly maximize the profit for the aggregator and track the required reserve provision trajectory from the collection of even a small number of flexible users. The proposed research is generalizable towards many resource scheduling problems with uncertainty that arise in the context of transportation, communication, and other engineering dynamical systems.
Broader Impacts:
Once successful, this project will provide a systematic approach for obtaining spinning reserve at much
less cost from flexible end user resources in a provably reliable and environmentally sustainable way.
This team will introduce new course modules on the topic of data-driven online learning in dynamical systems, which closely integrates reinforcement learning, dynamical control, and optimization for more than 200 undergraduate and graduate students currently enrolled in related areas courses at Texas A&M.
This team will continue the strong track record of engaging undergraduate students for research, in particular the under-representative groups.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CALIFORNIA, IRVINEUniversity of California-IrvineTryphon T Georgiou(949) 824-9966tryphon@uci.eduEfi Foufoula-Georgiou09/19/2018$299,981$299,98109/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Search for dynamical dependencies and natural time-scales of physical processes1839441046705849071549000ENERGY,POWER,ADAPTIVE SYSRadhakisan S. Baheti(703) 292-8339rbaheti@nsf.gov141 Innovation Drive, Ste 250IrvineCA92617-3213IrvineUS45University of California-IrvineS3230 Engineering GatewayIrvineCA92697-3975IrvineUS45A fundamental problem in physical sciences and engineering is to identify dependencies and dynamical relations between interacting processes for understanding causal relationships and advancing predictive modeling. Indeed, historically, such dependences often formed the basis of physical laws. The abundance of large data-sets about complex natural or engineered systems in our modern technological world, has brought a sense of urgency to the need for reliable and versatile machine learning tools to detect relations between processes. The starting point of the project is the realization that often the observational time scale at which data is collected may not be the native time scale at which interactions occur and thus sampling might obfuscate the nature of such relations. Indeed, linear dynamical relations between continuous-time processes may not be readily detectable from data collected at any finite sampling rate. This project will develop methodologies that will allow to fully recover sought relations between processes at the natural time-scale from data at a (typically coarser) observational time-scale. Theory and statistical learning tools that will be developed for that purpose will be applied to geophysical processes, such as identifying relationships between climate variables using a suite of observations from ground and multi-satellite sensors at different spatio-temporal scales.
When relations between variables are dynamic (i.e., the interaction relies on memory in the system), sampling hides the nature of dynamical dependencies. Specifically, in linear stochastic processes, dynamical dependencies between vector-valued processes are reflected in the nullity of the power spectral density matrix when this is estimated at the natural time-scale of the process. At the observational sampling rate, the corresponding nullity no longer relates to the structure of the dynamical relations. Yet, with proper analysis the dynamical relations can be recovered by projecting sample-models to the natural time-scale of the processes involved. In fact, for linear stochastic processes there is a fastest process time-scale that is consistent with the coarser scale observational data, and it is at that fine scale that models can be projected via solving suitable algebraic equations. At any coarser scale, dynamical dependencies cannot be readily detected. The project will focus on how to learn and recover the natural time-space scale at which dynamical dependencies must be sought. Statistical learning tools will be developed and applied to geophysical data as proof of concept.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MINNESOTA STATE COLLEGES AND UNIVERSITIESSouthwest Minnesota State UniversityDaniel Kaiser(507) 537-6163dan.kaiser@smsu.eduShushuang Man, Kourosh Mortezapour09/19/2018$168,822$168,82210/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Broadening Participation and Building Pathways in Computer Science (CS) through Concurrent Enrollment1836990879165306064754757STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.gov1501 State StreetMarshallMN56258-1598MarshallUS07Southwest Minnesota State UniversityMN56258-1598MarshallUS07This project studies the implementation and outcomes of Concurrent Enrollment (CE) programs as a vehicle for broadening participation in high school to college pathways in Computer Science (CS). The Mobile Computer Science Principles (Mobile CSP) project at the College of St. Scholastica, an established curriculum endorsed by the College Board for its alignment with the Advanced Placement (AP) CSP framework, has formed a Research-Practitioner Partnership (RPP) with CE programs at Capital Community College in Hartford, Connecticut and Southwest Minnesota State University in Minnesota and with partner school districts in each state. The RPP project explores whether CS through CE can broaden the high school to college pathway in computing disciplines for those traditionally underrepresented in these fields: female, underrepresented minority, and low-SES students. While the AP CSP course has enrolled a more diverse group of students than previous AP CS courses, it is not as diverse as other AP courses. CE programs appear to have better penetration than AP among schools that predominantly serve underrepresented minorities and low-SES students, showing promise for broadening participation in other disciplines and encouraging college matriculation.
By implementing and studying CS through CE in two different contexts (rural and low-SES in Minnesota and urban, diverse, and low-SES in Connecticut), the project contributes to transforming the educational pathways in CS in a variety of contexts and to understanding the supports and barriers to implementing CSP as CE with a broadening-participation goal. This project provides professional development and support of 40 high school teachers to teach a CE version of the Mobile CSP course among partnering school districts over the course of 3 years. The goals of this RPP project are (1) to examine and address the supports and barriers to implementing and sustaining Mobile CSP as a concurrent enrollment course and (2) to study whether a CE implementation of the CSP course broadens participation in computing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THESUNY at BuffaloMatthew Knepley(716) 645-0747knepley@buffalo.edu09/19/2018$215,715$215,71308/01/201707/31/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSI2-SSI: Collaborative Research: Scalable Infrastructure for Enabling Multiscale and Multiphysics Applications in Fluid Dynamics, Solid Mechanics, and Fluid-Structure Interaction1836797038633251020657151Software InstitutesRajiv Ramnath(703) 292-4776rramnath@nsf.gov520 Lee EntranceAmherstNY14228-2567BuffaloUS26SUNY at Buffalo520 Lee EntranceAmherstNY14228-2567BuffaloUS26Many biological and biomedical systems involve the interaction of a flexible structure and a fluid. These systems range from the writhing and coiling of DNA, to the beating and pumping of cilia and flagella, to the flow of blood in the body, to the locomotion of fish, insects, and birds. This project aims to develop advanced software infrastructure for performing dynamic computer simulations of such biological and biomedical systems. To facilitate the deployment of this software in a range of scientific and engineering applications, this project will develop new software capabilities in concert with new computer models that use the software. Specific application domains to be advanced in this project include models of aquatic locomotion that can be used to understand the neural control of movement and ultimately to develop new treatments for neurological pathologies such as spinal cord injuries, and models that simulate the interaction between the electrophysiology of the heart and the contractions of the heart that pump blood throughout the body, which could lead to improved approaches to treating heart disease. The software to be developed within the project is freely available online and is used by a number of independent research groups in a variety of scientific and engineering domains. It is being actively used in projects that model different aspects of cardiovascular dynamics, such as platelet aggregation and the dynamics of natural and prosthetic heart valves, and in projects that study other biological problems, including cancer dynamics, insect flight, aquatic locomotion, and the dynamics of phytoplankton. The software is also being applied to non-biological problems, including nanoscale models of colloidal suspensions and models of active particles. The improved methods and software to be developed in this project will thereby have a broad and sustained impact on a large number of ongoing research efforts in the biological and biomedical sciences and other scientific and engineering disciplines.
The immersed boundary (IB) method is a broadly applicable framework for modeling and simulating fluid-structure interaction (FSI). The IB method was introduced to model the fluid dynamics of heart valves, and subsequent development initially focused on simulating cardiac fluid dynamics. This methodology is broadly useful, however, and has been applied to a variety of problems in which a fluid flow interacts with immersed structures, including elastic bodies, bodies with known or prescribed deformational kinematics, and rigid bodies. Extensions of the IB method have also been developed to model electrophysiological systems and systems with chemically active structures. To improve the efficiency of the IB method, the PI has developed adaptive versions of the IB method that employ structured adaptive mesh refinement (AMR) to deploy high spatial resolution only where needed. These methods have been implemented within the IBAMR software framework, which provides parallel implementations of the IB method and its extensions that leverage high-quality computational libraries including SAMRAI, PETSc, and libMesh. This project will further extend the IBAMR software by implementing modeling and discretization technologies required by the research applications of current and prospective users of the software, by developing improved solver infrastructure facilitated by the implementation of native support for structured AMR discretizations in the PETSc library, and by integrating with existing high-quality software tools for model development, deployment, and analysis. IBAMR is freely distributed online and is used within a number of independent research groups both to the further development of the IB method and also to its application to simulate diverse problems in fluid dynamics and FSI. By enhancing IBAMR, this project will also enhance the ability of these and other researchers to construct detailed models without requiring those researchers to develop the significant software infrastructure needed to perform such simulations. This project will also develop general-purpose support for AMR discretizations in PETSc, a software library with thousands of active users, ~400 downloads per month, and numerous applications. The work of this project will help to grow the IBAMR user community of students and researchers by developing UI tools for building models, running simulations, and analyzing results. Students will be actively engaged in all aspects of the project, including code, method, and model development.NORTH CAROLINA AGRICULTURAL AND TECHNICAL STATE UNIVERSITYNorth Carolina Agricultural & Technical State UniversityAli Karimoddini(336) 285-3313akarimod@ncat.eduAbolghasem Shahbazi, Leila Hashemi Beni09/19/2018$596,143$596,14310/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITExcellence in Research: Developing a Robust, Distributed, and Automated Sensing and Control System for Smart Agriculture1832110071576482142363428SPECIAL PROJECTS - CISEDavid Corman(703) 292-8950dcorman@nsf.gov1601 E. Market StreetGreensboroNC27411-0001GreensboroUS06North Carolina Agricultural & Technical State University1601 E. Market StreetGreensboroNC27411-0001GreensboroUS06To accommodate rapidly growing food demands and increase the quality and quantity of agricultural production, it is necessary to improve farming management practices and technological developments in agricultural fields. This project will synergize expertise in Control, Robotics, Remote Sensing, and Agricultural Engineering to develop new approaches for automated monitoring of smart agricultural systems as an important class of cyber-physical systems (CPSs). This award supports fundamental research to develop innovative techniques for smart agricultural systems by employing a distributed airborne networked sensor system for a team of Unmanned Aerial Vehicles (UAVs) to survey a farm. Unlike traditional crop management methods that use ground operators or vehicles for monitoring farms, the proposed approach for airborne monitoring of agricultural fields minimizes deployment of on-the-ground operations, avoiding damaging crops on healthy parts of the farms.
The objectives of this project are (1) developing a distributed airborne monitoring system for surveying farms to detect possible zones of crop damage or nutrition deficiency, and (2) implementing and demonstrating the developed methods for coordination of UAVs for agricultural applications over the North Carolina Agricultural and Technical State University (NC A&T) farm. To achieve these objectives, an optimal planning technique will be developed for coordinating UAVs while incorporating their physical constraints and safety considerations, ensuring a complete survey of the farm and respecting sensing requirements. An automated decision-making technique will be developed to process the collected imagery information and detect the problem spots in the farm and their size and severity. Integrated with the proposed research is an innovative education and outreach plan that will engage a diverse range of students, farmers, and local community members in STEM-relevant activities and agritechnological aspects of this project to increase public awareness on using new technologies for further development of precision agriculture.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MOREHOUSE COLLEGE (INC.)Morehouse CollegeKinnis Gosha(470) 639-0634kinnis.gosha@morehouse.edu09/19/2018$992,892$992,89210/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITExcellence in Research: Evaluating the Use of Virtual Mentoring for HBCU Undergraduates in Computer Science1831964075861773075861773BROADENING PARTIC IN COMPUTINGFay Payton(703) 292-8950fpayton@nsf.gov830 Westview Drive S WAtlantaGA30314-3773AtlantaUS05Morehouse College830 Westview Drive, S.W.AtlantaGA30314-3773AtlantaUS05Morehouse College and Alabama A&M University proposes a collaborative research project to explore the use of avatars, formally known as embodied conversational agents, to provide career mentoring for undergraduate computer science majors who are considering pursuing a graduate degree in computing. The study will include participating students from ten different Historically Black Colleges and Universities (HBCUs). African Americans with terminal degrees in computer science are scarce, however HBCUs have a strong history of producing African American students who go on to get advanced degrees in computing. Research in this field will enable effective mentors in computer science to scale their best practices to a larger percentage of undergraduate students at HBCUs. This project will also fund the development of formal collaboration between Morehouse College and the Online Masters in Computer Science Program at the Georgia Institute of Technology. This groundbreaking program will allow the Principal Investigator to serve as the thesis advisor for Masters students at Georgia Tech while they are trained as researchers at Morehouse College.
This project will investigate the barriers faced by African American students when deciding on pursuing advanced degrees in computing as well as how intelligent virtual mentors affect their decision. It will examine what is the most effective way for an embodied conversational agent to interact with these specific group of students. Once completed, the findings from this study will be used to expand to other underrepresented groups to provide career mentoring for an assortment of science careers. Additionally, the findings from this research will help to build the research capacity at two HBCUs, Morehouse College and Alabama A&M University.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.SIPPA SOLUTIONS LLCSIPPA Solutions LLCMichael Wassil(215) 341-6538mjwassil@aol.comBon K Sy09/19/2018$711,189$711,18909/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSTTR Phase II: Self-Health Management Informatics Platform: Improving Patient Engagement in Care Delivery1831214079179856STTR PHASE IINancy Kamei(703) 292-7236nkamei@nsf.gov28-38 211 streetBaysideNY11360-2523BaysideUS06Queens College/City University of NY65-30 Kissena BlvdFlushingNY11367-1575FlushingUS06The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is a patient-centric engagement process that offers the best chance for enabling a scalable approach towards achieving the triple aim of improving care quality and outcomes, controlling health care costs and utilization, and increasing patient satisfaction. Currently the national healthcare cost is estimated at $3.2 trillion. Until patients could be engaged to take ownership of their health, advancement in pharmacological interventions through medications will not be able to achieve optimal care outcomes, and the healthcare cost and utilization will remain high. Engaging patients in self-management activities that are in alignment with the motivation indicators not only improves patient experience and satisfaction, but contributes to collecting big data for linking motivation to behavioral therapy --- resulting in an effect essential to improving population health and advancing personalized precision.
This Small Business Technology Transfer (STTR) Phase II project is a patient-centric engagement process MISA (Measure-Integrate-Share-Act). While well-established behavior models such as the Theory of Planned Behavior (TPB) and Information-Motivation-Behavioral Skill (IMB) have been reported to show clinical efficacy, the novelty of this research is the application of Structure Equation Modeling to develop a quantitative behavior model. Quantitative behavior modeling is significant because it allows a rigorous assessment of the model in terms of goodness of fit and statistical power. Furthermore, such model provides the patented SIPPA analytic engine a basis to predict the software services that are in alignment with the motivation indicators of a patient users in order to effectively engage them in self-health management of chronic conditions, and to promote behavioral change for healthy lifestyle.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BIOINFOEXPERTS LLCBioinfoexperts, LLCSusanna L Lamers(985) 413-0455susanna@bioinfox.com09/19/2018$735,056$735,05609/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: An Interactive Graphical Application for Next-Generation Surveillance of Hospital-Acquired Infections using Whole Genome Sequencing and Advanced Analytics1830867608519067SMALL BUSINESS PHASE IIRuth M. Shuman(703) 292-2160rshuman@nsf.govPO BOX 693ThibodauxLA70301-4904ThibodauxUS06Bioinfoexperts, LLC718 Bayou LaneThibodauxLA70301-4904ThibodauxUS06The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be a user-friendly and scalable infection control surveillance software platform using advanced biotech and data analytics for monitoring hospital-acquired infection. There is a significant clinical problem in hospitals, where 1 in 25 people who check in will develop a hospital acquired infection. Currently, hospital infection control practitioners (ICPs) have few analytical tools to identify the source of these infections, which can be deadly and cost the health care industry an estimate of $45 billion year. The innovation under development harnesses advanced epidemiological approaches in an easy-to-use application that will enable ICPs to use bacterial genetics as a means to monitor infectious spread within their system so that their sources can be eliminated.
The intellectual merit of this SBIR Phase II proposal is to develop an infection control surveillance software system using whole-genome sequencing of pathogens and advanced data analytics. The innovation addresses the critical lack of accessible genetic analysis applications designed for local infection control surveillance. Hospitals are observing ever increasing rates of antibiotic resistant infections. These are expensive, endanger patients, and are becoming harder to trace as medical care becomes more complex and spread over multiple facilities. Unfortunately, ICPs have few new tools, other than best hygiene practices, to reduce their mounting infection rates. Decades of research has revealed that epidemiological surveillance using genetic analysis provides a robust level of pathogen traceability; however, this knowledge has not been transferred into hospitals where it is critically needed, due to a lack of technical infrastructure and analytical accessibility. In this Phase II project, the goal is to complete the development of a software application that will enable ICPs to easily and accurately process bacterial genetic data in their own offices and generate rich, meaningful and easy to interpret reports concerning bacterial spread in their networks. ICPs will be warned when infection sources relate to each other, suggesting that a deeper investigation is needed. The result is that infection sources, which are currently missed, will be proactively identified and targeted.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE, THEUniversity of North Carolina at CharlotteTino Hofmann(704) 687-0991thofmann@uncc.eduThomas J Suleski, Yong Zhang, Menelaos Poutous, Ishwar Aggarwal09/19/2018$440,546$440,54610/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Development of an in-situ controlled Atomic Layer Deposition Tool (iCALD) for the Preparation of 3D Photonic Materials with Ultrahigh Aspect Ratios1828430066300096142363428MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.gov9201 University City BoulevardCHARLOTTENC28223-0001CharlotteUS12University of North Carolina at CharlotteNC28223-0001CharlotteUS12Optical materials composed of three-dimensional structures with ultra-high aspect ratios and coated with ultra-thin conformal layers enable a vast array of active and passive devices and components operating in the infrared and terahertz spectral range. Applications for these materials include environmental sensors with unprecedented sensitivity and multifunctional coatings to enhance three-dimensional micro-optical structures. The proposed in-situ controlled, atomic layer deposition (iCALD) instrument which will be developed at the University of North Carolina (UNC) at Charlotte and integrated in the cleanroom facility of the Center for Optoelectronics and Optical Communications will enable the fabrication of these optical materials. The ability to conformally coat structures with virtually arbitrary geometries enabled by the iCALD instrument will transform the use and scope of materials, structures, and optical devices, synthesized and fabricated using the existing cleanroom facilities. The iCALD instrument will enable research by over 40 faculty members from five departments across the UNC Charlotte campus, their students, and national and international collaborators. In addition, this unique instrument will be accessible for research organized in two NSF-funded Industry/University Cooperative Research Centers (I/UCRCs), the Center for Metamaterials and the Center for Freeform Optics. Through these Centers the iCALD development will lead to new opportunities for industry funded research projects and directly benefit more than 30 industry partners nationwide. The Optics Center together with the two I/UCRCs create an environment where the developed iCALD instrument will have a very significant impact due to its potential for commercialization of research results, along with enabling advanced training of MS and PhD students.
The project aims to develop this unique iCALD instrument for the synthesis of three-dimensional photonic materials. This new class of materials is composed of three-dimensional structures with ultra-high aspect ratios, coated with ultra-thin conformal layers. The preparation of conformal coatings for such structures and surfaces using atomic layer deposition (ALD) techniques requires the precise control of numerous crucial ALD process parameters to ensure quality, thickness, and conformity of the ultra-thin films. It is therefore imperative to control the ALD process parameters using layer thickness and conformity information obtained from non-contact, in-situ, measurement techniques. The iCALD instrument will allow in-situ monitoring and control of the layer-by-layer deposition process by using an innovative in-situ Mueller matrix ellipsometer operating at infrared wavelengths. The iCALD instrument will enable the accurate control of ultra-thin coatings, with sub-nanometer accuracy, deposited onto structures with feature sizes on the order of several hundred nanometers. The iCALD instrument thereby will allow the fabrication of novel infrared and terahertz photonic materials with unprecedented accuracy. Based on these novel three-dimensional photonic materials, a vast array of active and passive devices and components operating in the infrared and terahertz spectral range can be made. In addition, the iCALD instrument will provide valuable insights about layer-by-layer deposition onto structures with arbitrary geometries, which have not been demonstrated experimentally yet. The controlled deposition and in-situ monitoring capabilities developed by this project will further expand crucial understanding of the atomic layer deposition process required for the fabrication of structures with ultra-high aspect ratios. Significant improvement of the optical material properties of three-dimensional photonic materials enabled by this instrument is anticipated.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITYVirginia Polytechnic Institute and State UniversityRolf Mueller(540) 231-6005rolf.mueller@vt.eduAmos L Abbott, Alexander Leonessa, John Socha, Hongxiao Zhu09/19/2018$249,666$249,66610/01/201809/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Development of a System for High-Resolution Uninterrupted Capture of Complex Animal Motions1828280003137015003133790MAJOR RESEARCH INSTRUMENTATIONJoanne D. Culbertson(703) 292-8260jculbert@nsf.govSponsored Programs 0170BLACKSBURGVA24061-0001BlacksburgUS09Virginia Polytechnic Institute and State University1075 Life Science CirBlacksburgVA24061-1016BlacksburgUS09This major research instrumentation award supports the development of an integrated camera array that will be customized to meet the challenges of capturing fast and highly complex animal motions--providing an enabling tool for fundamental research to understand and model the dynamics of motion. The instrument will permit uninterrupted motion tracking for hundreds of points on an animal as it executes even the most complex motions, such as midair somersaults that bats perform in pursuit of prey. The unprecedented detail, quality, and quantity of the data to be generated will provide the basis for new fundamental research into how animals use freedom of movement to attain unmatched levels of performance in maneuverability and energy efficiency. The large volume of quantitative data produced by the instrument will bring data-intensive methods--from non-linear dynamics and machine learning-- to bear on the field of animal motion. A deeper understanding of the principles behind animal motion will be key to the development of next-generation mobile robots that can handle unconstrained, natural environments. These highly dexterous, mobile robots will enhance productivity in applications such as manufacturing, health care, disaster response, precision agriculture, forestry and environmental monitoring and clean-up. This instrument will also enable fundamental research on the motion of man-made structures, such as the complex dynamic motions inherent in flutter in aerodynamic systems. Knowledge gleaned from this instrument will also help veterinarians to diagnose disease and pain from animals' motion patterns. Graduate and undergraduate students will be involved in instrumentation development and the instrumentation will enable interdisciplinary research training opportunities in engineering and biology.
The instrument will combine high spatial and temporal resolution with the ability to view a moving animal from many different angles at the same time. It will consist of 48 high-speed video cameras that can deliver a 1280x1024-pixel image resolution at 1057-Hz frame rate. High-quality illumination will be provided by 8 specialized lights so that no part of a moving animal will ever be hidden from view. All cameras in the array will be synchronized (precision < 10 nanoseconds) and operated automatically to allow for efficient capture of large motion data sets. A recording of 5 seconds, for example, will result in over 250,000 images with 332 Gigabytes of raw data. The project team's automated image processing methods will allow reliable tracking of several hundred landmark points across such large image sets. The instrument and its accompanying suite of software tools will be used for the study of previously unexplained animal motion capabilities such as the highly articulated flight of bats, gliding of snakes, and lizards running on vertical substrates.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF UNION COLLEGE IN THE TOWN OF SCHENECTADY IN THE STATE OF NEW YORKUnion CollegeJohn A Rieffel(518) 388-6062rieffelj@union.eduLeo J Fleishman, Nicholas J Webb, Jennifer A Currey, Scott D Kirkton09/19/2018$272,430$272,43010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of a High Resolution High Speed 3D Motion Tracking System for Multi-Disciplinary Research and Research Training1827495059375584059375584MAJOR RESEARCH INSTRUMENTATIONJoanne D. Culbertson(703) 292-8260jculbert@nsf.gov807 Union StreetSchenectadyNY12308-3103SchenectadyUS20Union College807 Union StreetSchenectadyNY12308-3103SchenectadyUS20This Major Research Instrumentation (MRI) award supports the acquisition of a versatile high speed, high precision 3D motion tracking system to enable fundamental research and education in biomechanics, dynamics and controls, robotics, neuroscience and biology. Greater understanding of animal motions and communication will enable design of robots with more versatile movement patterns and that can be more effective partners with humans in activities ranging from disaster recovery to health care and manufacturing. It will also provide the basis for new treatments for joint injuries and strategies to mitigate damage from osteoarthritis. This 3D motion capture system will be the centerpiece of a common space in which student and faculty researchers can engage in interdisciplinary collaborations. The acquisition will integrate high speed high precision motion tracking techniques into undergraduate STEM research and teaching, along with new tools, methods, and environments to foster the development of future researchers. Targeted programs at the university will enhance the participation of underrepresented groups.
The 3D motion capture system is built around 20 Oqus 7+ cameras, each capable of a sustained data rate of 3.6 Gigapixels/sec -- allowing for frame rates and resolutions ranging from 12 Megapixels at 300fps to 3 Megapixels at 1100fps. The high-resolution and high-speed motion is needed to capture animals' complex, fast, and often subtle motion patterns for a better understanding of how body size affects locomotion, how injuries affect gait, and the role of motion in social interactions. The instrumentation can be configured into different size arenas to investigate a wide variety of issues, ranging from how soft systems learn to leverage their material properties to produce fast, dynamic and resilient behaviors (large set up) to smaller capture arenas with tracking of dozens of 1mm markers at sub-millimeter resolution to understand the complex relationship between joint loading and structural changes in bone.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ROCHESTER INSTITUTE OF TECHNOLOGY (INC)Rochester Institute of TechLuis Herrera(585) 475-7987lcheee@rit.edu09/19/2018$242,338$242,33809/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Hierarchical Intelligent and Adaptive Techniques to Enable Resilient DC Power Systems1809957002223642002223642ENERGY,POWER,ADAPTIVE SYSAnil Pahwa(703) 292-2285apahwa@nsf.gov1 LOMB MEMORIAL DRROCHESTERNY14623-5603RochesterUS25Rochester Institute of TechNY14623-5603RochesterUS25As the adoption of energy sources and loads with inherent dc voltage continues to increase, an electric system based on dc power can offer tremendous advantages over ac, with higher efficiency, less power conversion stages, smaller footprint, and higher reliability. For these reasons, dc power systems and microgrids are now used in electric vehicles, ships, aircraft, and in rural areas. However, electrical faults in dc power networks can lead to extremely dangerous situations which are more difficult to interrupt than their ac counterparts, particularly due to the lack of zero voltage crossings. Moreover, high impedance faults in the form of electrical arcs, such as those caused by loose connections or chafed wires, are very difficult to detect because of the low fault current. The high penetration of electronics loads with advanced controllers make the fault detection and localization even more challenging. To increase the safety and resiliency of dc based systems, the proposed project will address these technical challenges in detecting high impedance faults in dc power systems by developing intelligent and adaptive fault detection, localization, and isolation techniques that are built upon a comprehensive and systematic fault modeling and characterization study. These techniques can significantly improve the performance of existing and future dc systems to enable their wide adoption at larger scales, which can provide efficient and reliable interfaces to many renewable resources, energy storage units, and modern electronic loads and align with the nation's initiatives in using clean and green energy. This project is intrinsically multidisciplinary by bringing advanced and exciting modern control theories, artificial intelligence, and signal processing techniques into electric power engineering. The tasks in this project involve a wide range of expertise and experience from software simulation and control algorithms to hardware testing; from circuit level study to system level implementation, which provides a unique and high quality training opportunity for future engineers. The proposed educational activities will also broaden participation of women and other under-represented students.
The goal of the proposed research is to develop fault detection, localization, and isolation techniques for modern dc power systems through a hierarchical approach with intelligent and adaptive functionalities. It addresses the most challenging issues in the protection of dc power systems with a systematic and transformative effort. The fault modeling and characterization study of the proposed project will generate fundamental and critical knowledge of high impedance faults in modern application settings through comprehensive experimental and analytical approaches. The proposed high impedance fault detection and localization techniques will take into account the effect of advanced controllers through dynamic parameter estimation. The adaptive and integrated fault detection and localization schemes to be developed will significantly enhance the existing protection system design and online stability assessment methodologies by adopting modern nonlinear control theory and artificial intelligence tools. The proposed research is expected to produce significant results of both theoretical and practical values to the field of dc power systems. When successfully completed, the project has the potential to revolutionize the control and protection aspects of dc power systems, minimizing the adverse impact of high impedance faults and constant power loads. The proposed techniques can be applied to dc systems in different scales ranging from isolated dc distribution networks to interconnected dc microgrids, to improve the fault protection effectiveness and therefore their resiliency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THESUNY at BuffaloXiu Yao(716) 645-2634xiuyao@buffalo.edu09/19/2018$282,023$282,02309/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Hierarchical Intelligent and Adaptive Techniques to Enable Resilient DC Power Systems1809839038633251020657151ENERGY,POWER,ADAPTIVE SYSAnil Pahwa(703) 292-2285apahwa@nsf.gov520 Lee EntranceAmherstNY14228-2567BuffaloUS26Department of Electrical Engineering, University at BuffaloDavis HallWilliamsvilleNY14260-2500BuffaloUS26As the adoption of energy sources and loads with inherent dc voltage continues to increase, an electric system based on dc power can offer tremendous advantages over ac, with higher efficiency, less power conversion stages, smaller footprint, and higher reliability. For these reasons, dc power systems and microgrids are now used in electric vehicles, ships, aircraft, and in rural areas. However, electrical faults in dc power networks can lead to extremely dangerous situations which are more difficult to interrupt than their ac counterparts, particularly due to the lack of zero voltage crossings. Moreover, high impedance faults in the form of electrical arcs, such as those caused by loose connections or chafed wires, are very difficult to detect because of the low fault current. The high penetration of electronics loads with advanced controllers make the fault detection and localization even more challenging. To increase the safety and resiliency of dc based systems, the proposed project will address these technical challenges in detecting high impedance faults in dc power systems by developing intelligent and adaptive fault detection, localization, and isolation techniques that are built upon a comprehensive and systematic fault modeling and characterization study. These techniques can significantly improve the performance of existing and future dc systems to enable their wide adoption at larger scales, which can provide efficient and reliable interfaces to many renewable resources, energy storage units, and modern electronic loads and align with the nation's initiatives in using clean and green energy. This project is intrinsically multidisciplinary by bringing advanced and exciting modern control theories, artificial intelligence, and signal processing techniques into electric power engineering. The tasks in this project involve a wide range of expertise and experience from software simulation and control algorithms to hardware testing; from circuit level study to system level implementation, which provides a unique and high quality training opportunity for future engineers. The proposed educational activities will also broaden participation of women and other under-represented students.
The goal of the proposed research is to develop fault detection, localization, and isolation techniques for modern dc power systems through a hierarchical approach with intelligent and adaptive functionalities. It addresses the most challenging issues in the protection of dc power systems with a systematic and transformative effort. The fault modeling and characterization study of the proposed project will generate fundamental and critical knowledge of high impedance faults in modern application settings through comprehensive experimental and analytical approaches. The proposed high impedance fault detection and localization techniques will take into account the effect of advanced controllers through dynamic parameter estimation. The adaptive and integrated fault detection and localization schemes to be developed will significantly enhance the existing protection system design and online stability assessment methodologies by adopting modern nonlinear control theory and artificial intelligence tools. The proposed research is expected to produce significant results of both theoretical and practical values to the field of dc power systems. When successfully completed, the project has the potential to revolutionize the control and protection aspects of dc power systems, minimizing the adverse impact of high impedance faults and constant power loads. The proposed techniques can be applied to dc systems in different scales ranging from isolated dc distribution networks to interconnected dc microgrids, to improve the fault protection effectiveness and therefore their resiliency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MONTANA STATE UNIVERSITY, INCMontana State UniversityIoannis Roudas(406) 994-5960ioannis.roudas@montana.edu09/19/2018$100,000$100,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITGOALI: Collaborative Research: An Experimentally Validated Simulation Framework for Next-Generation Plastic Optical Fiber-based Systems on Airplanes1809043625447982079602596COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov309 MONTANA HALLBOZEMANMT59717-2470BozemanUS00Montana State University619 Cobleigh Hall, P.O. Box 1737BozemanMT59717-3780BozemanUS00GOALI: Collaborative Research: An Experimentally-Validated Simulation Framework for Next-Generation Plastic Optical Fiber-based Systems on Airplanes
This research project seeks to develop an experimentally-validated simulation framework that will help investigate and design Plastic Optical Fiber (POF)-based communication systems and networks for airplanes. The main participants are The College of Staten Island (CSI/CUNY), Montana State University-Bozeman (MSU), and The City College of New York (CCNY/CUNY). It will also involve an international collaboration with the University of Zaragoza (UZ), Spain, and a GOALI component with the world-leader in avionics, The Boeing Co. Avionic communication systems are currently undergoing a radical transformation in both the commercial and military sectors. The former (commercial), the focus of this project, exhibits an increasing need for high-speed communication due to emerging applications for the traveling public, as well as higher operational needs for the ultra-modern aircraft that are being deployed. In addition, aging aircraft wiring poses a significant threat to aircrafts, as electrical wires have proven to be one of the major factors leading to airplane failures. Therefore, there is an ongoing migration of avionic data buses from copper to fiber-based networks, since the latter exhibit high transmission capacity and high electromagnetic immunity. The investigators have suggested POF as a suitable transmission medium for next-generation avionic communication systems on commercial aircrafts due to its ease of handling, light weight and high tolerance to vibration, among other benefits. While experimental results have demonstrated the feasibility of high-speed data transmission over different types of POFs, the modeling and simulation of POF-based systems is lagging behind. Therefore, the investigators will develop a comprehensive set of components and simulation techniques that empower engineers to systematically explore different designs before settling on a final custom solution for their particular system. They will also make a special effort to involve women and underrepresented groups in the effort since they traditionally are not exposed to avionic systems engineering.
The goal of the project is to study the use of POF in an airplane environment with an emphasis on system performance and high bit rate transmissions. Glass fiber has a number of problems when used as a transmission medium in short-reach networks such as avionic networks. It is mechanically weak and generally lacks bending ability. Also, the core diameter of single-mode glass optical fiber is small (~10mm) and it requires very precise handling techniques. Plastic optical fiber (POF), even with its high loss (~100-300 dB/km) and diffusion, can solve these problems since it is easier to handle and has a bending radius of about 5 mm, which can be a big benefit in avionics networks. Its larger core diameter (50 mm to 1 mm) enables easy connections using inexpensive connectors. The increased core diameter allows higher tolerance to vibrations and to dust particles that can totally obstruct light propagation in glass fibers. The investigators will cover three different types of POF: large-core (up to 1 mm) step-index plastic optical fiber (SI-POF), multicore step-index plastic optical fiber (MC SI-POF), and graded-index plastic optical fiber (GI-POF). There are existing simulation models that capture all the guided modes in multimode fibers with detailed spatial fields; however, they are not adequate for large-core fibers, where there are millions of propagation modes. The project intends to develop computationally-efficient models that circumvent the need for prohibitively long simulation times and excessive computer memory. The model validation, a critical component of the project, will be done via a combination of the state-of-the-art device characterization laboratory at the University of Zaragoza and a testbed at the College of Staten Island. Montana State University will primarily work on advanced modulation formats and digital signal processing algorithms. Boeing Co. will provide prototype devices and realistic system designs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PURDUE UNIVERSITYPurdue UniversityWenzhuo Wu(765) 494-1055wu966@purdue.eduPeide Ye09/19/2018$413,801$413,80110/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITScalable Nanomanufacturing of Large-area Two-dimensional Tellurene for High-performance Wearable Piezoelectric Devices1762698072051394072051394NANOMANUFACTURINGKhershed Cooper(703) 292-7017khcooper@nsf.govYoung HallWest LafayetteIN47907-2114West LafayetteUS04Purdue University315 North Grant StreetWest LafayetteIN47907-2023West LafayetteUS04Piezoelectric nanomaterials convert mechanical signals into electrical power and promise to revolutionize emerging self-powered technologies. Current methods for making piezoelectric nanomaterials are restricted by growth substrates, reaction pressure and temperature, which limits their economic manufacture. This award supports fundamental research to provide needed knowledge for the development of a low-temperature, substrate-free, scalable nanomanufacturing process. The novel process involves solution-based nanomanufacturing of a new piezoelectric nanomaterial, two-dimensional tellurene, with high productivity and high quality. Piezoelectric nanomaterials exhibit superior mechanical and piezoelectric properties to their bulk counterparts and are increasingly preferred for applications in energy, healthcare, sensors, and biomedical and wearable devices. Therefore, results from this research benefits the U.S. economy and society. This research involves several disciplines including manufacturing, materials science, electrical engineering, device physics, and data science. The multi-disciplinary approach helps broaden participation of women and underrepresented groups in research and positively impacts engineering education.
Hydrothermal solution process can overcome several limitations existing in nanomaterial manufacturing. These range from energy budget, scalability, environmental control, and working temperature. However, some scientific barriers are yet to be overcome to realize the full potential of the hydrothermal solution process for manufacturing of 2D nanomaterials. This research is will fill the knowledge gap on the mechanisms for the 2D tellurene formation during hydrothermal synthesis. The objectives are (1) to explore the unique advantage and capability of low-cost, scalable solution-based manufacturing for growth of tellurene nanomaterials with control over their production yield, morphology and dimensions, and (2) to uncover the process-structure-property-functionality relationships in designing, manufacturing, and integrating the tellurene-based wearable piezoelectric nanodevices. The research team will pursue a physics-based theoretical model to predict the structural and piezoelectric properties of tellurene manufactured by the hydrothermal process and conduct experiments to verify the model. The research team will test the hypothesis that surfactant type and concentration are the determining factors for controlling the thickness and hence the piezoelectric behavior of tellurene, and in so doing, will establish the relationships between process parameters and material functionality (e.g., piezoelectricity) in hydrothermal nanomanufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CALIFORNIA, LOS ANGELESUniversity of California-Los AngelesKaren E Sears(217) 898-3011ksears@ucla.edu09/18/2018$230,869$230,86907/01/201708/31/2019GrantNSF4900490047.074040100 NSF RESEARCH & RELATED ACTIVITDimensions: Collaborative Research: Discovering genomic and developmental mechanisms that underlie sensory innovations critical to adaptive diversification1854469092530369071549000Dimensions of BiodiversitySimon Malcomber(703) 292-8227smalcomb@nsf.gov10889 Wilshire BoulevardLOS ANGELESCA90095-1406Los AngelesUS33University of California-Los Angeles621 Charles E. Young Drive SouthLOS ANGELESCA90095-8348Los AngelesUS33All animals must sense their environment and other organisms to find food, avoid threats, and find partners. The ability of some individuals to locate food and mates more effectively than others can open opportunities for them to leave many more descendants. And yet, multiple advanced sensory systems seldom evolve in the same species despite the advantages they may confer, suggesting there are physical limits to developing several specialized senses. This project focuses on a diverse group of tropical bats in which various species evolved acute, specialized hearing, supersensitive eyes, the ability to smell subtle plant chemicals, or highly developed vomeronasal systems (thought to contribute to mating and social hierarchy). This project will compare approximately 2000 genes involved in vision, hearing, olfaction and the vomeronasal system in more than 150 bat species. To find out how some of these genes contribute to developing distinct sensory systems, their actions will be studied in the lab. This research will uncover the role of specific genes in the acquisition of specialized senses, test whether the size of the head limits the number of specialized sensory structures a species can have, and discover how sensory adaptations contribute to the diversity of species through time.
This project will uncover the evolution of genes and structures of the auditory, visual, and olfactory and vomeronasal systems in a large superfamily of bats characterized by diverse sensory adaptations associated with specific diets. Analyses of gene evolution will be used to test the hypothesis that sensory innovations arise through gene duplication and positive selection. Measurements of gene expression from tissues collected in the field, and experiments to express key bat genes in developing embryos will be used to elucidate how genes shape adaptive sensory structures. Comparative analyses of detailed measurements of the size of sensory structures will evaluate trade-offs between sensory systems and the way these may limit diversity of diets or species. State-of-the art methods to quantify relationships between gene and trait evolution and species diversity will be used to discover the impact of sensory adaptation on species diversity through time. This research will illuminate the main biological forces in the genome, during embryonic development, and in anatomical structures that contribute to the success of species in adapting to their ever-challenging environment.GEORGIA TECH RESEARCH CORPORATIONGeorgia Tech Research CorporationWendy Newstetter(404) 894-8805wendy.newstetter@bme.gatech.edu09/18/2018$50,000$50,00001/15/201906/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITI-CORPs: Kalmed Healthcare1853069097394084097394084I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.govOffice of Sponsored ProgramsAtlantaGA30332-0420AtlantaUS05Georiga Institute of Technology225 North Ave.AtlantaGA30332-0420AtlantaUS05The broader impact/commercial potential of the I-Corps project is to optimize the efficiency of blood testing by minimizing costs, providing faster results, offering a more painless solution and increasing the convenience of where one?s blood is tested. A direct patient-to-lab interface allows for a new way of testing. This envisioned stand-alone testing kiosk could reach diabetes patients in remote, rural settings both domestically and internationally who have limited access to a healthcare facility. Our diagnostic testing solution could eliminate the need of a healthcare professional allowing blood collection and testing to be a very easy task to accomplish. Our product has the potential to incentivize more patients with blood-related diseases to get their blood tested, leading to quicker diagnosis and a better treatment plan.
This I-Corps project offers a blood collection device that utilizes a capillary extraction method, which has the potential to extract blood within seconds, rather than the standard venous draw, which takes longer and requires a healthcare professional. This method may be more painless than typical capillary extractions as the intended site of usage for lancet devices is the finger, which contains more sensitive pain receptors. In some instances we have received input that the constant pricking of a finger has become a nuisance which is why the site of action chosen has been the arm. The issue of vein accuracy is further a contributing factor to the blood collection device functionality as the issue is solved via the capillary method.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TEXAS AT ARLINGTONUniversity of Texas at ArlingtonAnimesh Chakravarthy(316) 978-6328animesh.chakravarthy@wichita.edu09/18/2018$356,980$356,98008/01/201802/28/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCAREER: Generalizations in Obstacle Avoidance Theory1851817064234610042000273ROBUST INTELLIGENCEReid Simmons(703) 292-4767resimmon@nsf.gov701 S Nedderman Dr, Box 19145ArlingtonTX76019-0145ArlingtonUS06The University of Texas at ArlingtonArlingtonTX76019-0018ArlingtonUS06This project develops a theoretical framework that enables an analytical characterization of guidance laws for obstacle avoidance, accompanied by an experimental validation of these laws. This has significant implications since the obstacle avoidance problem is an important component of the path planning problem, which appears in several diverse fields including robotics, autonomous air, ground and underwater vehicles, computer animation, molecular motion, autonomous wheelchairs, spacecraft avoiding space debris, robotic surgery, assistance aids for the blind, etc. The guidance laws designed are particularly applicable for real-time implementation of precise path planning in cluttered dynamic environments such as those containing robot manipulators, humanoid robots, vehicles flying in formation and other high-dimensional spaces wherein the agents have no a priori information about their environment. A robustness analysis of the designed guidance laws to various uncertainties such as sensor noise, data delays and data dropouts is performed, followed by an experimental validation wherein the guidance laws are coded on microcontroller platforms in a resource-efficient manner and implemented on small-scale robotic ground and air vehicles. The expected results include guidance laws suitable for collision avoidance of obstacles of various, possibly time-varying, shapes moving in high-dimensional stochastic environments, along with a postulation of the safety guarantees of these guidance laws. This project also performs multiple outreach activities and introduces new curriculum that promote the education and applications of robotics, and these activities are conducted in levels starting from K-12 all the way through undergraduate and graduate level engineering education.UNIVERSITY OF TEXAS AT SAN ANTONIO, THEUniversity of Texas at San AntonioAmir JafariAmir.Jafari@utsa.edu09/18/2018$50,000$50,00009/15/201802/28/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITI-CORPS: A Treadmill with Adjustable Stiffness with integrated measurement systems for rehabilitation applications1850898800189185042000273I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.govOne UTSA CircleSan AntonioTX78249-1644San AntonioUS20University of Texas at San AntonioOne UTSA CircleSan AntonioTX78249-1644San AntonioUS20The proposed product spans the following innovation areas. Development of new technology: 1- Novel method is presented to design and fabricate a treadmill solution by which flexibility of the walking surface can be controlled. This treadmill has the ability to bilaterally adjust the surface stiffness in a purely vertical direction, regardless of the relative location of the person with respect to the treadmill. By using strong stiffness adjustment motors and properly selecting a short lever, the stiffness can be changed very quickly. 2- Development of new rehabilitation approach: feasibility of a theory-driven rehabilitation approach will be proven that can lead to successful clinical trials for after-stroke patients. The treadmill is integrated with a motion capture and energy consumption system that can provide real-time data regarding the performance of the patients. This can help a therapist to quickly find the optimal tuning for a patient.
The proposed research advances the field of mobility rehabilitation through introducing the possibility of adjusting the stiffness of the walking surface. As of 2015, there are more than 18.2 million people with mobility impairment in the US. Among them, the majority are post-stroke patients. In the US, a stroke occurs every 40 seconds and the aggregate lifetime cost of first strokes is about $40 billion per year. In addition, nearly 40% of people age 65 and older have a walking disability. Any rehabilitation method that can enhance independent mobility of these populations would have a huge impact on their quality of life as well as reduce economic burden on the them, their families, insurance companies and the government. This product can be a solution to improve the walking capability of these people for community settings.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TEXAS TECH UNIVERSITY HEALTH SCIENCES CENTERTexas Tech University Health Science CenterCourtney M Queen(325) 696-0654courtney.m.queen@ttuhsc.edu09/18/2018$50,000$50,00009/15/201802/28/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITImaging Tools for the Early Detection of Burli Ulcer1850706609980727041367053I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.gov3601 4th Street, MS 6271LubbockTX79430-6271LubbockUS19Texas Tech University Health Science Center1650 Pine StreetAbileneTX79601-3053AbileneUS19This innovation demonstrates how advanced algorithm information technologies can transform the medical care delivery system by shifting the focus to early diagnosis. This technology identifies suspicious skin lesions as positive or negative for the structural properties of Buruli ulcers. Furthermore, this technique validates the classification system for other skin lesions which can be improved and expanded to include other types of skin diseases for humans, animals, and also plants. Point-of-care diagnostics for skin diseases have the potential to not only identify diseases in the early stages, but also create opportunities to initiate medical interventions in earlier stages of a disease, thereby reducing medical costs by treating diseases with antibiotic therapy instead of surgical interventions and eliminating any unnecessary pain and suffering resulting from complications of late-stage disease diagnosis. This innovation is critical for differential diagnosis, disease surveillance, collecting environmental contextual data, medication adherence, and advancing health literacy. This work is important because it contributes to a wider body of knowledge that seeks to validate algorithm development for point-of-care diagnostics, and ultimately improves access to healthcare for rural and hard-to-reach populations, also reducing barriers to care for otherwise stigmatizing and debilitating diseases.
Advancements in point-of-care diagnostics for neglected tropical diseases, and neglected infections of poverty represents an opportunity to decrease both the incidence and prevalence of debilitating and disfiguring diseases. These otherwise preventable diseases represent the most disability-adjusted life years lost. Representative of an interdisciplinary intervention, image diagnostics for skin diseases require the development of effective means for intervention design, management, and evaluation while enhancing the relationships and collaborations working internationally, across cultures, with community-based primary care, and to also include opportunities for incorporating telehealth to address access to care in resource-limited and hard-to-reach communities. Opportunities to more widely disseminate this research, and to include commercial potential expands the scope of this innovation and provides additional education and training opportunities for students of engineering and public health, but also for clinicians, and community-based healthcare providers. Successful implementation of point-of-care diagnostics for early stage disease detection advances the disciplines and allows for the translation of the innovation, analysis, synthesis, and interpretation of research for future education and training. Lastly, the advancement of this type of innovation has the ability to shift the medical system to early diagnosis reducing the overall disease burden of ill-health and disability due to late stage diagnosis of disease.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PHOENIX, CITY OFCity of PhoenixMark E Hartman(602) 256-4287mark.hartman@phoenix.gov09/18/2018$61,000$5,00009/15/201808/31/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITBelmont Forum Collaborative Research Food-Water-Energy Nexus: Globally and Locally-sustainable Food-Water-Energy Innovation in Urban Living Labs1832195965015832078984358INTERNATIONAL COORDINATION ACTMaria L. Uhle(703) 292-8500muhle@nsf.gov200 W Washington StPhoenixAZ85003-1611PhoenixUS07City of PhoenixAZ85003-1611PhoenixUS07Many cities across the globe are facing difficult challenges managing their food, water and energy systems. The challenges stem from the fact that the issues of food, water and energy are often tightly connected with each other, not only locally but also globally. This is known as the Food-Water-Energy (FWE) nexus. An effective solution to a local water problem may cause new local problems with food or energy, or cause new water problems at the global level. On a local scale, it is difficult to anticipate whether solutions to one issue in the nexus are sustainable across food, water and energy systems, both at the local and the global scale. Innovative solutions that encompass the nexus are particularly important to enable cities to better manage their food, water and energy systems and understand the benefits and tradeoffs for different solutions.
This award supports U.S. researchers participating in a project competitively selected by a 29-country initiative through the joint Belmont Forum- Joint Programming Initiative (JPI) Urban Europe. The Sustainable Urbanization Global Initiative (SUGI)/Food-Water-Energy Nexus is a multilateral initiative designed to support research projects that bring together the fragmented research and expertise across the globe to find innovative solutions to the Food-Water-Energy Nexus challenge. The call seeks to develop more resilient, applied urban solutions to benefit a much wider range of stakeholders. The rapid urbanization of the world's population underscores the importance of this focus. International partners were invited to develop solutions for this challenge. The funds requested will be used to support U.S. participants to cooperate in consortia that consist of partners from at least three of the participating countries and that bring together natural scientists, social scientists and research users (e.g., civil society, NGOs, and industry). Participants from other countries are funded through their national funding organizations.
This project seeks to develop a novel approach to produce innovative solutions to FWE challenges that are both locally and globally sustainable, through experiments in Urban Living Labs in Austria, Brazil, Germany Netherlands, South Africa, Sweden and the USA. Urban Living Labs are a forum for innovation, applied to the development of new products, systems, services and processes, employing working methods to integrate people into the entire development process as users and co-creator, to explore, examine, experiment, test and evaluate new ideas, scenarios, processes, systems, concepts and creative solutions in complex and real contexts. The project will involve a range of urban stakeholders early in the creative and evaluative processes of innovation, and the solutions produced will be tested for environmental soundness and economic viability and social acceptability and robustness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PRENOSIS, INC.Prenosis, Inc.Bobby Reddy(949) 246-3113bobby.reddy.jr@electrocyt.com09/18/2018$704,525$704,52510/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Point of Care Device for High Frequency Stratification of Patient Populations at Risk of Sepsis1831193079414131SMALL BUSINESS PHASE IIHenry Ahn(703) 292-7069hahn@nsf.gov210 Hazelwood Drive Ste 103ChampaignIL61822-7488ChampaignUS13Prenosis, Inc.210 Hazelwood Drive Ste 103ChampaignIL61822-7488ChampaignUS13Sepsis is a poorly understood clinical syndrome and is characterized by a dysregulation of the immune system?s response to infection. It is the leading cause of death and is the most expensive condition treated in U.S. hospitals, exerting a $20.3 billion burden annually, 5.2% of total costs to the healthcare system nationwide. Sepsis is highly time critical and every 1-hour delay in antibiotics is associated with a 3-7% increase in the odds of a poor outcome. There is currently a dire need for a tool that can quickly assess if a patient is at risk for sepsis. Such a tool would ideally gather any relevant information very quickly and provide a probability of sepsis directly back to the physician in less than 30 minutes. If this tool were available, a lot of the uncertainty revolving around early sepsis screening could be minimized. Outcomes such as mortality, readmission rate, length of stay, length of ICU stay, hospital cost, and compliance to Center for Medicare and Medicaid Services Core Measures could all be improved by such a tool.
The goal of the SBIR Phase I project was to establish the feasibility of a point of care sensor that can measure cells and proteins from a drop of blood for the eventual stratification of sepsis. In Phase II, work will continue with our manufacturing partners to design, optimize, and test a one-time-use cartridge and a portable reader for the simultaneous measurement of cells and proteins from a small volume of blood. The objective will be to develop a scalable technology platform, that can measure total white blood cell count, CD64 expression on neutrophils, and 2 proteins (IL-6, and PCT), simultaneously from the same drop of blood, and also be able to measure different proteins by changing the types of beads used in the assay. The goal is to allow physicians and healthcare providers to perform frequent measurements at the point of care, and to integrate the clinical and biological data to predict sepsis and organ dysfunction. The result of this project will be a fully functional reader and accompanying disposable cartridges for the measurement of these critical sepsis biomarkers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PATIENTSVOICES, LLCPatientsVoices, LLCMary Kay O'Connor(816) 866-0363maryk.oconnor@patientsvoices.net09/18/2018$691,183$691,18309/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Software for Developing Consumer-Driven Health Care Solutions1831160079407584SMALL BUSINESS PHASE IINancy Kamei(703) 292-7236nkamei@nsf.gov5317 NW Bluff WayKansas CityMO64152-1130ParkvilleUS06PatientsVoices, LLC1520 Clay StreetNorth Kansas CityMO64116-4126Kansas CityUS05The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that the technology provides health care systems with a very accurate view of what their patients experience during health care encounters - what is going well and importantly, what specific problems are frustrating patients. With this insight, providers are able to quickly and efficiently resolve issues. Patients are increasingly active in deciding where they receive care. As health care spending declines, providers find themselves competing for patients. To attract patients and drive market share, health systems must deliver not just excellent clinical care but also positive patient experiences. Patients that have a negative health care encounter often choose to go elsewhere. When they do, providers lose margin.
This Small Business Innovation Research (SBIR) Phase II project addresses the industry need for better insight on how to quickly and efficiently improve patient experiences. Surveys which are the norm in health care fail to deliver service failure details. The company's software goes beyond current text analysis solutions by automating the classification of patient feedback based on the ideas and sentiment expressed by patients. These results are converted into precise analytics and displayed in dashboards so front-line managers can quickly identify problems and make rapid improvements in patient experiences. Previously the company demonstrated the technical feasibility of its software by focusing on a narrow set of providers. This research will refine the software so that it is capable of analyzing patient feedback across a wide range of health care organizations. What operational changes will have the greatest, positive impact on patient loyalty and market share? Results from this project will answer that question for a broad range of health care organizations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MARYLANDUniversity of Maryland College ParkPaul Leisnham(301) 405-6269leisnham@umd.eduHubert J Montas, Sacoby M Wilson, Victoria Chanse, Amanda Rockler09/18/2018$1,499,833$1,499,83309/15/201802/28/2023GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCNH-L: Stormwater Management Across Urban Ecosystems: Diagnostic Tools and Community Engagement for Ecological Restoration, Equitable Community Development and Revitalization1824807790934285003256088DYN COUPLED NATURAL-HUMANRichard Yuretich(703) 292-4744ryuretic@nsf.gov3112 LEE BLDG 7809 Regents DriveCOLLEGE PARKMD20742-5141College ParkUS05University of Maryland College Park1459 Animal Sciences BldgCollege ParkMD20742-2315College ParkUS05Abstract
Excess nitrogen, phosphorous and sediment associated with urbanization is a threat to water quality and environmental health in many locations. This project will investigate how urban watersheds can be improved through better stormwater management. The research will examine two watersheds in Washington, DC and Baltimore, Maryland that possess different degrees of urban decay and revitalization. It will compare the effectiveness of different interventions, both technical and social, at reducing unhealthy processes and feedbacks between the environment and people. Specific research objectives and activities are to: (1) document neighborhood issues and needs in informing stormwater best-management practices; (2) evaluate stormwater volume and quality, flooding risk, trash accumulation, and mosquito production within the watersheds; (3) develop a tool that uses Geographic Information Systems (GIS) to guide watershed management; and 4) enhance community awareness and positive behaviors to improve water quality and protect urban green space. This project will develop and evaluate practices that foster sustainable water resources and help educate participants, from teachers to students to all residents, many of whom are racial and ethnic minorities and socially, economically, and educationally disadvantaged, on processes and strategies involved in addressing water sustainability. It will train interdisciplinary graduate and undergraduate students in interactive social, biological, and ecosystem sciences as they relate to water resources sustainability, neighborhood planning, mosquito ecology, and environmental justice.
This project addresses key biophysical and social drivers of nutrient pollution in watersheds, and the associated factors related to the socio-ecological matrix of the built environment, urban decay and revitalization, and resident attitudes and behaviors. Coupled stormwater-human dynamics have the potential to become a signature model for developing new socio-ecological theory about urban ecosystems, improving quality of life and environmental justice, and initiating sustained community-oriented management of natural systems. This project integrates the required expertise and theory from social science, city planning, hydrological science, ecology, adult and youth education, and environmental justice to explicitly characterize stormwater-human systems. This research combines socio-demographic measures of human behavior and stormwater quantity and quality to dynamically model pollution hot spots, assess the efficacy of interventions, and explicitly quantify the feedback of these variables. It represents an advance in the knowledge of coupled pollution-human dynamics in an urban context and provide valuable information for urban planning, remediation, and public health.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF NOTRE DAME DU LACUniversity of Notre DameRobert Nerenberg(574) 631-4098Nerenberg.1@nd.eduKyle Bibby, Dwight Houweling09/18/2018$330,078$330,07810/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITGOALI: Effect of Hydroxylamine on the Structure and Function of Nitrifying Biofilms1805406824910376048994727ENVIRONMENTAL ENGINEERINGKarl Rockne(703) 292-5347krockne@nsf.gov940 Grace HallNOTRE DAMEIN46556-5708Notre DameUS02University of Notre Dame940 Grace HallNotre DameIN46556-5708Notre DameUS02Wastewater treatment is needed for environmental protection, but most treatment processes are very energy intensive. A recently developed biological treatment process, called partial nitritation-anammox (PNA), can save energy. However, it is difficult to use in most treatment processes because it requires the suppression of some bacteria commonly found in wastewater. This research explores a new type of reactor configuration, along with the addition of the chemical hydroylamine, that may allow PNA to be effectively used for wastewater treatment. The research involves a collaboration with SUEZ, an industrial partner. It will train undergraduate and graduate students, as well as a post-doctoral researcher, and will include outreach to a community college with a new program in vertical farms.
A collaborative study between the University of Notre Dame and SUEZ, a leader in membrane technologies, is proposed for a novel biofilm-based treatment technology that allows control of the internal physical and chemical environment in the biofilm. This method enables partial nitritation in existing wastewater treatment plants, a critical bottleneck in the energy-efficient PNA process. Furthermore, this biofilm environment control could enable other critical functions not currently possible in wastewater treatment, potentially serving as a disruptive technology. A key part of the new treatment process is the supply of chemicals to biofilms. In particular, this project will investigate how the supply of hydroxylamine, an intermediate of ammonia oxidizing bacteria (AOB) that can stimulate AOB growth and suppress nitrite-oxidizing bacteria (NOB) will alter the effectiveness of the PNA process. Researchers will first characterize the effects of hydroxylamine on the growth kinetics of AOB and NOB. Then the effects of hydroxylamine spikes on the structure and function of nitrifying biofilms will be explored using micro sensors, molecular tools, and imaging. An advanced biofilm model will be used to predict the best strategies for PNA. Finally, pilot-scale studies will be carried out to determine the process effectiveness in the field and to gather data and recommendations for scale-up and potential commercialization. This is the first research to study the effects of hydroxylamine on the microbial community structure of nitrifying biofilms. By determining the kinetics of AOB and NOB during and following exposure to hydroxylamine, this work will provide insights into fundamental inhibition mechanisms. This information will also provide a foundation for predicting the behavior of biofilms intermittently exposed to hydroxylamine. By studying mixed-culture biofilms with microsensors and molecular tools, the research could reveal potential niches for novel bacteria. The modeling and biofilm experiments will help engineer more effective water treatment processes. Workshops, lectures, and seminars at the University of Notre Dame and SUEZ will disseminate knowledge on biofilm research and process development to undergraduate, graduate, and Ivy Tech Community College students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF THE SCIENCES IN PHILADELPHIAUniversity of the Sciences in PhiladelphiaShivendra V Sahi(215) 596-7417s.sahi@usciences.edu09/18/2018$456,959$456,95808/31/201708/31/2019GrantNSF4900490047.074040100 NSF RESEARCH & RELATED ACTIVITRUI: Functional characterization of gold responsive genes and development of plant based system for efficient synthesis of gold nano-particles1854250079497681079497681Systems and Synthetic BiologyAnthony Garza(703) 292-8440aggarza@nsf.gov600 South 43rd StreetPhiladelphiaPA19104-4418PhiladelphiaUS02University of the Sciences in Philadelphia600 S. 43rd StreetPhiladelphiaPA19104-4418PhiladelphiaUS02Nanotechnology is a fast emerging area that is attracting immense research interest. Gold nanoparticles, which are the focus of this project, have properties that are very different than bulk metal and have applications in a variety of areas, including medicine, heavy industry, and information and communication technologies. The aim of this project is to understand the mechanism of gold uptake and gold nanoparticle production in plants. Once the molecular mechanism of gold nanoparticle biosynthesis is deciphered, a plant-based system can be easily manipulated for efficient production of these nanoparticles for downstream applications. In contrast to conventional methods, which generate tons of hazardous materials, this eco-friendly method of gold nanoparticle production will generate minimal wastes, and thus have a minimal impact on the environment. Many undergraduate student researchers will be active participants on this project and will gain hands-on experience of this cutting-edge nano-biotechnology.
The goal of this project is to gain a comprehensive understanding of the mechanism of gold uptake and assimilation in plants by identifying the genes involved in gold nanoparticle biosynthesis. A combination of molecular, biochemical and physiological approaches will be used for this project. The long-term goal of this project is to develop transgenic approaches to further enhance the biosynthesis of gold nanoparticle of different shapes and sizes for potential downstream applications. This project will also extend an international research collaboration with scientists from the Indian Agricultural Research Institute (IARI) in New Delhi, India. This research project will: (i) train and mentor at least 15 undergraduate students for independent research and critical thinking skills, and (ii) provide opportunities for oral and written communication of research findings through presentations, and peer-reviewed publications. Through close mentoring and careful monitoring of progress, we will motivate and prepare students to pursue graduate degrees and to build careers in STEM discipline. Students will also have opportunity to visit IARI laboratories, where they will have an opportunity to perform research, interact and collaborate with foreign students, post-docs and scientists. Finally, it is anticipated that the study will take the field of nanogold technology a step closer to commercial realism.UNIVERSITY OF ALABAMAUniversity of Alabama TuscaloosaRobert Morganrmorgan@cba.ua.edu09/18/2018$50,000$50,00001/15/201906/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITI-Corps: RFID Surgical Tagging System for Early Detection of Bone Screw Loosening1852943045632635808245794I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.gov801 University Blvd.TuscaloosaAL35487-0005US07University of Alabama TuscaloosaAL35478-0104PetersonUS07The broader impact/commercial potential of this I-Corps project is a cost-effective method for preemptively monitoring bone screw loosening. The current medical diagnostic market is dominated by expensive and time-consuming scans and procedures such as X-rays, CT scans, and MRI scans. These scans are costly and strain medical resources causing delays in the delivery of healthcare. The project will explore the commercial feasibility of streamlining the field of medicine, specifically in the diagnosis of bone screw loosening, through implantable diagnostic tools. Given the trend of preventative health care and growing need for healthcare cost reduction, developing a cost-effective method to diagnose bone screw loosening could augment both of these efforts.
This I-Corps project is to ascertain which customer segment would value the improved diagnostic efficiency of the RFID surgical tagging system such that its commercial application could be realized. The RFID surgical tagging system is a novel method to detect bone screw loosening through an implantable tag placed on surgical screws. This system utilizes low-cost components and an intuitive, yet unique design based on previously patented technology. The original patented technology is used to determine the screw status of hardware on large manufacturing equipment such as rockets. The surgical tagging system yields actionable screw status data in a faster and more easily accessible manner compared to current diagnostic measures for bone screw loosening. Based on the above competencies, the RFID surgical tagging system provides a viable alternative to current diagnostic scans. Through the I-Corps cohort, the team will explore and discover which customer segment values this technology in the medical diagnostic market.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BOARD OF REGENTS NEVADA SYSTEM OF HIGHER EDUCATIONUniversity of Nevada Las VegasAlexander Paz(702) 688-3878apaz@unlv.edu09/18/2018$50,000$50,00009/15/201802/28/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITI-Corps: Costumer Discovery for Demand-responsive Transverse Rumble Strips1852940098377336067808063I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.gov4505 MARYLAND PARKWAYLas VegasNV89154-1055Las VegasUS01University of Nevada Las Vegas4505 S. Maryland Parkway, PO Boxlas vegasNV89154-4007Las VegasUS01The broader impact/commercial potential of this I-Corps project is to provide a safety device to reduce traffic crashes, injuries, and fatalities. Existing alternative technologies alone are unable to address the existing demand. In the U.S, nearly 6,000 pedestrian fatalities and 70,000 pedestrian injuries occur each year. From 2016 to 2017 there was a 27% increase in pedestrian fatalities. Additionally, 130,000 schools across the United States need enhanced techniques to increase driver alertness. In 2017, over 2,000 crashes resulting in 289 deaths occurred at rail crossings. A strong global demand exists for the proposed traffic safety device because there are not alternatives with similar effectiveness. Because the proposed device will be active only when required, it has a much broader range of applications compared to alternative technologies. For example, the proposed devise provides redundancy in the case of autonomous vehicles to minimize the likelihood of crashes due to failures and/or malfunction in the detection or navigation systems. That is, the proposed device provides an alternative communication channel to alert the autonomous vehicle to slow down or stop. The concept behind the proposed device to enhance safety can be extended to other environments such as construction sites.
This I-Corps project is about customer discovery for a Demand-Responsive Transverse Rumble Strip (DRTRS) mechanism, which becomes active (lowers an array of strips) only when necessary to alert drivers and vehicles through noise and vibration of downstream risks. Permanent transverse rumble strips are mainly used on approaches to intersections, toll plazas, horizontal curves, and work zones to slow down traffic. Traditional transverse rumble strips have been shown to be effective. However, drivers become familiar with their location over time and their effectiveness tends to diminish. Unnecessary noise, vehicle deterioration, and pavement wear out are additional concerns associated with traditional transverse rumble strips. The intellectual merits of our research are: (i) an effective and deployable DRTRS mechanism that addresses the above issues and (ii) evaluation of its effectiveness and required maintenance. The proposed intellectual merits required addressing simultaneously significant challenges including operability and reliability under extreme environmental and heterogeneous traffic conditions, small depth to minimize affecting the integrity of the existing pavement, easy and rapid maintenance and replacement, minimal maintenance schedules, and durability under snow plow operations. In addition, this project is helping us improve our understanding of using acoustic and haptic senses to prevent accidents.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ASSOCIATED UNIVERSITIES, INC.Associated Universities Inc/National Radio Astronomy ObservatoryAdam Cohen(202) 462-1676acohen@aui.eduAnthony Beasley09/18/2018$2,500,000$2,500,00009/01/201812/31/2019Cooperative AgreementsNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITVery Long Baseline Array Fiber Optics Data Access Supplement1849364074801689078859701NRAOJoseph E. Pesce(703) 292-7373jpesce@nsf.gov1400 16TH ST NW STE 730WASHINGTONDC20036-6225WashingtonUS00Associated Universities Inc/National Radio Astronomy ObservatoryDC20036-2252WashingtonUS00This proposal describes plans to complete the connection of all VLBA stations to an optical fiber network. Upon completion the VLBA data network capacity will be increased to 200 Mbps. Such capacity will allow improved diagnostic and time-critical observing capabilities. Upgrades to the VLBA data network is the first step in a three-phased approach to allow real-time observations. Improved connectivity that optical fiber provides will increase the scientific utility of the VLBA for the US and global scientific community.
Improving the data capabilities of the VLBA by installing/operating optical fiber to all sites will greatly enhance its capabilities, opening additional areas of VLBA research and extend the distance ranges, both within the Galaxy and throughout the Universe, at which the VLBA can make unique scientific contributions. The VLBA is uniquely situated to increase participation of traditionally under-served and underrepresented communities in the full spectrum of fields associated with radio astronomy. With 10 sites located across eight states and the U.S. Virgin Islands, the VLBA offers research and educational exchange opportunities to a broad cross section of the U.S. student population, including students who live and study in areas of the country in which targeted efforts are made to broaden participation of diverse individuals in STEM education, training, and professional development. In addition, VLBA observations are vital to maintaining awareness of Earth's orientation in space, a parameter of key importance in operation of the Global Positioning System for example.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.KANSAS STATE UNIVERSITYKansas State UniversityB Jan Middendorf(785) 532-3480jmiddend@ksu.eduVara Prasad, Cynthia A Shuman09/18/2018$99,047$99,04710/01/201809/30/2019GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITInternational Network-to-Network (N2N) Stakeholder Collaboration Workshop: Solutions to Accelerate Research, Leverage Resources, and Maximize Synergies1842111929773554041146432AccelNet - Accelerating ResearClaire Hemingway(703) 292-7135chemingw@nsf.gov2 FAIRCHILD HALLManhattanKS66506-1100ManhattanUS01Kansas State UniversityKS66506-1103ManhattanUS01International research collaborations are supported using a variety of partnership models. However, what works under what circumstances and why is poorly documented. This workshop will engage key thought leaders from across the globe in a dynamic discussion of the critical issues related to international partnerships and collaborations to leverage resources, maximize synergies, and accelerate research. Workshop participants will examine existing models of international funding partnerships and contribute to an action plan. The workshop activities will promote partnerships, establish shared learning, and strengthen connections to support the implementation of international network-to-network collaborations responsive to global research to benefit society.
The aim of this workshop is to identify the overarching issues related to international network-to-network partnerships, categorize and prioritize these issues, and develop potential solutions to tackle these challenges. Representatives from stakeholders in international research networks who are knowledgeable about or have an interest in building network-to-network partnerships will come together in a facilitated discussion. The workshop provides a structure that supports interaction and collaboration of key stakeholders to co-create a partnership model to support international networks of networks. A formalized report of the workshop will (1) summarize effective partnership models, (2) capture strengths, weaknesses, opportunities, and threats to international network-to-network collaborations, and (3) propose an action plan. The workshop and report will increase awareness of critical issues related to strengthening international research collaborations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF MICHIGANUniversity of Michigan Ann ArborTed Brader(734) 936-1777tbrader@umich.edu09/18/2018$6,517,166$860,51109/15/201808/31/2022GrantNSF4900490047.075040100 NSF RESEARCH & RELATED ACTIVITANES FACE-to-FACE: The American National Election Studies 2018-20211835971073133571073133571POLITICAL SCIENCEBrian D. Humes(703) 292-7284bhumes@nsf.gov3003 South State St. Room 1062Ann ArborMI48109-1274Ann ArborUS12University of Michigan Ann Arbor3003 S. State St.Ann ArborMI48109-1274Ann ArborUS12Since the 2016 election, Americans have found themselves in a period of remarkable uncertainty and change. Some worry about threats to the nation's democracy while others are concerned that the U.S. president is unfairly targeted by the media and "witch hunt" investigations. What do Americans make of all this and how do they want to go forward? The American National Election Studies (ANES) surveys are an essential tool for answering such questions. Understanding the preferences of its citizens is the hallmark of a healthy, functioning democracy, and since 1948 the ANES has been the gold standard for measuring the opinions of the public and a leading resource in understanding voting behavior in the United States. The upcoming presidential election in 2020 is shaping up to be a defining moment in American history. Trust in democratic institutions has been declining at an alarming rate among the American public. Challenges, as well as defenses, of those institutions are coming from many directions. New and existing questions on the ANES survey will allow researchers to understand the sources of growing American discontent, explain misunderstandings between elected officials the public, and identify opportunities for bridging the country?s political and social divisions in the future.
Understanding the preferences of citizens is the hallmark of a healthy, functioning democracy, and the American National Election Studies (ANES) time series has been the gold standard for gauging and assessing the connection between public opinion and voting behavior in the U.S. We propose to conduct the 2020 face-to-face ANES surveys, the most comprehensive and careful study of how Americans evaluate their government, form opinions about major issues of the day, participate in politics, and choose which candidates to support, and thereby extend a time series that dates back to 1948. Specifically, we propose to collect data in 2020 on a national probability sample of respondents in two waves of in-person interviews (before and after the election). The content and design of these surveys will be informed by two major pilot surveys and a number of small-scale pilots. In an era where response rates for phone surveys have dipped below 10 percent and where most online surveys still face daunting issues with respect to representativeness, the ANES survey offers reliable measurement of social, economic, and political attitudes in the context of American elections. The negativity and polarization of our political environment make the need for non-partisan, scientifically-valid survey research more pressing than ever. This is what ANES offers, while also providing unparalleled time series data that puts the nature of our current politics into appropriate historical context.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.SIGMA XI, THE SCIENTIFIC RESEARCH HONOR SOCIETY, INC.Sigma Xi, The Scientific Research Honor Society, Inc.Dena K Plemmons(858) 752-9585dena.plemmons@ucr.eduStephanie J Bird, Daniel R Vasgird09/18/2018$162,451$162,45110/01/201809/30/2020GrantNSF4900490047.075040100 NSF RESEARCH & RELATED ACTIVITStandard: RR: Authors Without Borders: Continuing Investigation of International Authorship Norms among Scientists and Engineers1835237080839129Cultivating Cultures of EthicaJohn Parker(703) 292-5034joparker@nsf.govP O Box 13975Research Triangle ParkNC27709-3975DurhamUS04Sigma XiP O Box 13975 3200 Chapel Hill NResearch Triangle ParkNC27709-3975DurhamUS04In science, authorship of a research article or report is widely used as an indicator of scientific success. This can result in significant conflict in any collaboration, but international collaborations pose unique challenges with respect to ethical issues and conflict related to scientific authorship. Social norms about scientific authorship differ markedly across national contexts in ways that may create confusion or conflict to an extent not typical in domestic forms of scientific collaboration. This project will explore these issues by studying international norms surrounding scientific authorship, sources and explanations for conflict surrounding authorship in international collaborations, and the extent to which the society in which a researcher lives shapes their ideas about authorship practices. In doing so it will identify roadblocks to effective international collaboration, and develop a set of best practices and a set of guidelines to address sources of conflict in scientific authorship. Findings will also be used to develop educational materials on these issues for domestic and international scientists.
This cross-national study of authorship norms and of conflict surrounding issues of scientific authorship will develop a social survey for national and international dissemination across a wide array of scientific disciplines. This project will expand upon a previous study by these investigators in which they researched these issues in two disciplines across four nations. Surveys for this project will be based on those from the pilot study and will be translated into thirteen languages and administered to scientists working in eighty-two nations in a wide-variety of disciplines. The survey will consist of demographic questions, open-ended responses, and Likert-scale survey items measuring levels of agreement and disagreement about authorship practices in international collaborations. The survey will yield qualitative and quantitative data that will be analyzed using established qualitative and quantitative analysis software. Findings from the study will be disseminated in publications and conferences, and through their integration into existing training modules for promoting responsible conduct of research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.LOCAL FIRST ARIZONA FOUNDATIONLocal First Arizona FoundationKimber Lanningkimber@localfirstaz.com09/18/2018$61,901$61,90109/15/201808/31/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITBelmont Forum Collaborative Research Food-Water-Energy Nexus: Globally and Locally-sustainable Food-Water-Energy Innovation in Urban Living Labs1832203966399680INTERNATIONAL COORDINATION ACTMaria L. Uhle(703) 292-8500muhle@nsf.gov407 E. Roosevelt StreetPhoenixAZ85004-1918PhoenixUS07Local First Arizona FoundationAZ85004-1918PhoenixUS07Many cities across the globe are facing difficult challenges managing their food, water and energy systems. The challenges stem from the fact that the issues of food, water and energy are often tightly connected with each other, not only locally but also globally. This is known as the Food-Water-Energy (FWE) nexus. An effective solution to a local water problem may cause new local problems with food or energy, or cause new water problems at the global level. On a local scale, it is difficult to anticipate whether solutions to one issue in the nexus are sustainable across food, water and energy systems, both at the local and the global scale. Innovative solutions that encompass the nexus are particularly important to enable cities to better manage their food, water and energy systems and understand the benefits and tradeoffs for different solutions.
This award supports U.S. researchers participating in a project competitively selected by a 29-country initiative through the joint Belmont Forum- Joint Programming Initiative (JPI) Urban Europe. The Sustainable Urbanization Global Initiative (SUGI)/Food-Water-Energy Nexus is a multilateral initiative designed to support research projects that bring together the fragmented research and expertise across the globe to find innovative solutions to the Food-Water-Energy Nexus challenge. The call seeks to develop more resilient, applied urban solutions to benefit a much wider range of stakeholders. The rapid urbanization of the world's population underscores the importance of this focus. International partners were invited to develop solutions for this challenge. The funds requested will be used to support U.S. participants to cooperate in consortia that consist of partners from at least three of the participating countries and that bring together natural scientists, social scientists and research users (e.g., civil society, NGOs, and industry). Participants from other countries are funded through their national funding organizations.
This project seeks to develop a novel approach to produce innovative solutions to FWE challenges that are both locally and globally sustainable, through experiments in Urban Living Labs in Austria, Brazil, Germany Netherlands, South Africa, Sweden and the USA. Urban Living Labs are a forum for innovation, applied to the development of new products, systems, services and processes, employing working methods to integrate people into the entire development process as users and co-creator, to explore, examine, experiment, test and evaluate new ideas, scenarios, processes, systems, concepts and creative solutions in complex and real contexts. The project will involve a range of urban stakeholders early in the creative and evaluative processes of innovation, and the solutions produced will be tested for environmental soundness and economic viability and social acceptability and robustness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TOLEDO, THEUniversity of ToledoTerry P Bigioni(419) 530-4095Terry.Bigioni@utoledo.edu09/18/2018$50,000$50,00009/15/201802/28/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITNSF I-Corps: Silver materials for antimicrobial coatings1853675051623734051623734I-CorpsNancy Kamei(703) 292-7236nkamei@nsf.gov2801 W Bancroft St., MS 218TOLEDOOH43606-3390ToledoUS09University of Toledo2801 W Bancroft St., MS 218ToledoOH43606-3390ToledoUS09The broader impact/commercial potential of this I-Corps project is to provide a new means of creating broad-spectrum antimicrobial fabric treatments with a low barrier to entry for manufacturers. This technology promises to deliver antimicrobial coatings at lower overall economic and environmental costs, by reducing solvent usage, waste, and coating loss. Antimicrobial treatments are already used in medicine, as anti-infective treatments of bandages, catheters, and other medical items, and in garments and textiles, as anti-odor treatments. The lower barrier to entry for garment manufacturers is expected to enable more widespread adoption of the technology, which in turn will reduce material and energy waste from excessive laundering and save consumers money. The technology can be adapted to a wide range of fiber types and can be applied without specialized equipment, facilitating the integration into existing manufacturing processes and giving manufacturers access to premium market segments with minimal upfront investment.
This I-Corps project will help improve the market penetration of antimicrobial treatments, which in turn will provide consumers with superior garment performance at reduced environmental and economic costs. The technology uses a new form of soluble silver metal, developed by prior NSF funded research, and an innovative method to coat a variety of different fiber types with bioactive silver, which enables the antimicrobial coatings to be applied at any stage in the manufacturing process. Proof of concept has been demonstrated with basic prototyping, but development of the technology for specific markets and applications demands a better understanding of customer needs. This I-Corps team project is aimed at discovering those customer needs, through extensive customer interviews, in order to inform the development and engineering of products that meet each particular market specific need that is identified.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.KANDRA LABS, INC.KANDRA LABS INCTimothy G Abbott(703) 859-1830tabbott@kandralabs.com09/18/2018$750,000$750,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Zulip threaded group chat1831273080356345SMALL BUSINESS PHASE IIPeter Atherton(703) 292-8772patherto@nsf.gov235 Berry St Ste 306San FranciscoCA94158-1629San FranciscoUS12KANDRA LABS INC235 Berry St, Suite 306San FranciscoCA94158-1646San FranciscoUS12The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will result from group chat technology that enables knowledge workers to collaborate more effectively than ever before. It is the first tool built that empowers users to efficiently carry out both real-time and asynchronous conversations in the same system, with each user reading only those conversations that are important to him or her. In particular, the technology empowers teams to make decisions in virtual meetings that take place asynchronously over periods of hours or days. This is in contrast with existing group chat technology, where conversations usually end as soon as someone starts talking about something else. This ability to conduct long running, virtual meetings is invaluable for large teams that need to coordinate work across different locations and time zones. Large, distributed teams are fast becoming the norm for how organizations operate, as instant communication and globalization make such teams the workforce of the future. Coordinating the efforts of such teams is a huge pain point for companies, and this technology is a leap in the state of the art in this space.
This Small Business Innovation Research (SBIR) Phase II project has three major research objectives: scaling the technology to teams of 10,000+ people; faithfully translating the user experience to mobile devices; and developing techniques for serving the needs of diverse deployments large and small. For scalability, one major area is "presence", telling each user who else is currently online. Presence data naturally grows with the number of pairs of users, therefore much faster than the number of users, and the company will need to develop algorithms to focus presence on significant connections between users. Among the unique challenges on mobile, the often-limited Internet connectivity demands algorithms that remember data previously fetched from the server to avoid asking for it again, carefully balanced with getting needed updates to never show out-of-date information to the user; the immediacy required for a great chat experience makes both horns of this dilemma especially sharp. Serving diverse deployments demands techniques for making software updates routine and seamless, a practice recently popularized in browsers and mobile apps but rarely accomplished to date in distributing server applications such as that described here.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF WISCONSIN SYSTEMUniversity of Wisconsin-MadisonKael D Hanson(608) 890-0540kael.hanson@icecube.wisc.eduDouglas F Cowen, Tyce R DeYoung, Dawn Williams09/18/2018$22,983,529$4,731,50610/01/201809/30/2023Cooperative AgreementsNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITIceCube Gen2 Phase 1: an IceCube Extension for Precision Neutrino Physics and Astrophysics1719277161202122041188822Particle Astrophysics/UndergroJames J. Whitmore(703) 292-8908jwhitmor@nsf.gov21 North Park StreetMADISONWI53715-1218MadisonUS02University of Wisconsin-Madison222 West Washington AveMadisonWI53703-2775MadisonUS02Embedded deep in the ice cap at the South Pole, the IceCube Neutrino Observatory (ICNO) is the world's unique, largest, and most sensitive high energy neutrino telescope. It is a one-billion-ton detector that uses the deep Antarctic ice as a medium to detect high energy atmospheric and astrophysical neutrinos. Most of the neutrinos observed by IceCube exhibit energies in the range expected for atmospheric neutrinos that originate from decays of elementary particles produced in extensive air showers by cosmic rays coming from nearby sectors of the Milky Way Galaxy. While these can be used to measure the fundamental properties of neutrinos, astrophysical neutrinos at higher energies are key probes of the high-energy phenomena in the Universe. Because of their unique properties, neutrinos pass almost freely through even dense volumes of space and are not deflected by galactic or extra-galactic magnetic fields and traverse the photon-filled universe unhindered. Thus, neutrinos provide direct information about the dynamics and interiors of the powerful cosmic objects that may be the origins of high energy cosmic rays: supernovae, black holes, pulsars, active galactic nuclei and other extreme extragalactic phenomena. This award will fund the deployment of seven additional strings of photon sensors in the deep, clear Antarctic ice at the bottom center of IceCube, forming the IceCube Gen2 Phase 1 extension ("Phase 1").
The availability of a deep-ice drill presents several opportunities to enhance the existing IceCube infrastructure for research and education. Deep ice drills will also allow for the possibility of deploying next-generation optical sensor technology prototypes within the existing IceCube operations framework at the U.S. Amundsen-Scott South Pole Station, presenting new opportunities for training a new cohort of international students and young scientists throughout the instrumentation development, production, and field deployment. The combination of astrophysics and the extreme polar climate attracts wide popular interest.
The new strings will use multi-PMT Digital Optical Modules (mDOMs), providing better directionality and more than double the photocathode area per module, at lower cost per unit area, than traditional IceCube DOMs. The mDOMs will be tightly integrated into the existing IceCube data acquisition framework, at marginal added long-term maintenance and operations expense. The new instrumentation will dramatically boost IceCube's performance at the 5 GeV energy scale, yielding over an order of magnitude more statistics than current samples, and enabling IceCube to perform the world's best measurement of tau neutrino appearance and the world's most stringent test of unitarity in the tau sector of the PMNS (Pontecorvo-Maki-Nakagawa-Sakata) matrix. This matrix describes all known neutrino oscillation behavior, and deviations from unitarity would be evidence for new physics. The strings will feature new calibration devices that would allow to better model the optical properties of the ice, reducing systematic uncertainties in the tau neutrino appearance measurement and enhancing IceCube's already strong contribution to multimessenger astrophysics via improved reconstruction of the direction of high energy cascade events for searches of point sources and enhanced identification of PeV-scale tau neutrinos. High energy tau neutrinos are essentially guaranteed to be astrophysical in origin, and they are a unique probe of neutrino oscillation physics over ultra-long baselines, providing powerful complementarity with Phase 1's atmospheric tau neutrino appearance measurement at lower energies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TENNESSEEUniversity of Tennessee KnoxvilleMichela Taufer(302) 690-7845taufer@utk.edu09/18/2018$438,105$438,10406/01/201806/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCIF21 DIBBs: PD: Cyberinfrastructure Tools for Precision Agriculture in the 21st Century1854312003387891003387891DATANETAmy Walton(703) 292-4538awalton@nsf.gov1 CIRCLE PARKKNOXVILLETN37996-0003KnoxvilleUS02University of Tennessee Knoxville1 Circle ParkKnoxvilleTN37996-0003KnoxvilleUS02This interdisciplinary project applies computer science approaches and computational resources to large multidimensional environmental datasets, and synthesizes this information into finer resolution, spatially explicit products that can be systematically analyzed with other variables. The main emphasis is ecoinformatics, a branch of informatics that analyzes ecological and environmental science variables such as information on landscapes, soils, climate, organisms, and ecosystems. The project focuses on synthesis/computational approaches for producing high-resolution soil moisture datasets, and the pilot application is precision agriculture. The effort combines analytical geospatial approaches, machine learning methods, and high performance computing (HPC) techniques to build cyberinfrastructure tools that can transform how ecoinformatics data is analyzed.
The investigators build upon publicly available data collections (soil moisture datasets, soil properties datasets, and topography datasets) to develop: (1) tools based on machine-learning techniques to downscale coarse-grained data to fine-grained datasets of soil moisture information; (2) tools based on HPC techniques to estimate the degree of confidence and the probabilities associated with the temporal intervals within which soil-moisture-base changes, trends, and patterns occur; and (3) data- and user- interfaces integrating data preprocessing to deal with data heterogeneity and inaccuracy, containerized environments to assure portability, and modeling techniques to represent temporal and spatial patterns of soil moisture dynamics. The tools will inform precision agriculture through the generation and use of unique information on soil moisture for the coterminous United States. Accessibility for field practitioners (e.g., local soil moisture information) is made possible through lightweight virtualization, mobile devices, and web applications.
This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Earth Sciences within the NSF Directorate for Geosciences.TEMPE, CITY OFCity of TempeBraden R Kay(480) 350-8867braden_kay@tempe.gov09/18/2018$61,900$33,45009/15/201808/31/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITBelmont Forum Collaborative Research Food-Water-Energy Nexus: Globally and Locally-sustainable Food-Water-Energy Innovation in Urban Living Labs1832233120327630074466814INTERNATIONAL COORDINATION ACTMaria L. Uhle(703) 292-8500muhle@nsf.gov31 East 5th StreetTempeAZ85281-3680TempeUS09City of Tempe31 5th StreetTempeAZ85281-3601TempeUS09Many cities across the globe are facing difficult challenges managing their food, water and energy systems. The challenges stem from the fact that the issues of food, water and energy are often tightly connected with each other, not only locally but also globally. This is known as the Food-Water-Energy (FWE) nexus. An effective solution to a local water problem may cause new local problems with food or energy, or cause new water problems at the global level. On a local scale, it is difficult to anticipate whether solutions to one issue in the nexus are sustainable across food, water and energy systems, both at the local and the global scale. Innovative solutions that encompass the nexus are particularly important to enable cities to better manage their food, water and energy systems and understand the benefits and tradeoffs for different solutions.
This award supports U.S. researchers participating in a project competitively selected by a 29-country initiative through the joint Belmont Forum- Joint Programming Initiative (JPI) Urban Europe. The Sustainable Urbanization Global Initiative (SUGI)/Food-Water-Energy Nexus is a multilateral initiative designed to support research projects that bring together the fragmented research and expertise across the globe to find innovative solutions to the Food-Water-Energy Nexus challenge. The call seeks to develop more resilient, applied urban solutions to benefit a much wider range of stakeholders. The rapid urbanization of the world's population underscores the importance of this focus. International partners were invited to develop solutions for this challenge. The funds requested will be used to support U.S. participants to cooperate in consortia that consist of partners from at least three of the participating countries and that bring together natural scientists, social scientists and research users (e.g., civil society, NGOs, and industry). Participants from other countries are funded through their national funding organizations.
This project seeks to develop a novel approach to produce innovative solutions to FWE challenges that are both locally and globally sustainable, through experiments in Urban Living Labs in Austria, Brazil, Germany Netherlands, South Africa, Sweden and the USA. Urban Living Labs are a forum for innovation, applied to the development of new products, systems, services and processes, employing working methods to integrate people into the entire development process as users and co-creator, to explore, examine, experiment, test and evaluate new ideas, scenarios, processes, systems, concepts and creative solutions in complex and real contexts. The project will involve a range of urban stakeholders early in the creative and evaluative processes of innovation, and the solutions produced will be tested for environmental soundness and economic viability and social acceptability and robustness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ARIZONA STATE UNIVERSITYArizona State UniversityLauren W Keeler(480) 965-5479Lauren.Withycombe@asu.eduArnim Wiek09/18/2018$319,771$109,22309/15/201808/31/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITBelmont Forum Collaborative Research Food-Water-Energy Nexus: Globally and Locally-sustainable Food-Water-Energy Innovation in Urban Living Labs1832196943360412806345658INTERNATIONAL COORDINATION ACTMaria L. Uhle(703) 292-8500muhle@nsf.govORSPATEMPEAZ85281-6011TempeUS09Arizona State UniversityPO Box 876011TempeAZ85287-6011TempeUS09Many cities across the globe are facing difficult challenges managing their food, water and energy systems. The challenges stem from the fact that the issues of food, water and energy are often tightly connected with each other, not only locally but also globally. This is known as the Food-Water-Energy (FWE) nexus. An effective solution to a local water problem may cause new local problems with food or energy, or cause new water problems at the global level. On a local scale, it is difficult to anticipate whether solutions to one issue in the nexus are sustainable across food, water and energy systems, both at the local and the global scale. Innovative solutions that encompass the nexus are particularly important to enable cities to better manage their food, water and energy systems and understand the benefits and tradeoffs for different solutions.
This award supports U.S. researchers participating in a project competitively selected by a 29-country initiative through the joint Belmont Forum- Joint Programming Initiative (JPI) Urban Europe. The Sustainable Urbanization Global Initiative (SUGI)/Food-Water-Energy Nexus is a multilateral initiative designed to support research projects that bring together the fragmented research and expertise across the globe to find innovative solutions to the Food-Water-Energy Nexus challenge. The call seeks to develop more resilient, applied urban solutions to benefit a much wider range of stakeholders. The rapid urbanization of the world's population underscores the importance of this focus. International partners were invited to develop solutions for this challenge. The funds requested will be used to support U.S. participants to cooperate in consortia that consist of partners from at least three of the participating countries and that bring together natural scientists, social scientists and research users (e.g., civil society, NGOs, and industry). Participants from other countries are funded through their national funding organizations.
This project seeks to develop a novel approach to produce innovative solutions to FWE challenges that are both locally and globally sustainable, through experiments in Urban Living Labs in Austria, Brazil, Germany Netherlands, South Africa, Sweden and the USA. Urban Living Labs are a forum for innovation, applied to the development of new products, systems, services and processes, employing working methods to integrate people into the entire development process as users and co-creator, to explore, examine, experiment, test and evaluate new ideas, scenarios, processes, systems, concepts and creative solutions in complex and real contexts. The project will involve a range of urban stakeholders early in the creative and evaluative processes of innovation, and the solutions produced will be tested for environmental soundness and economic viability and social acceptability and robustness.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MURA INC.MURA INC.Lingfei Meng(585) 967-4452meng@muravision.com09/18/2018$749,998$749,99809/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Advanced Computational Imaging System for 3D Surface Microgeometry and Reflectance Properties Measurement1831274080268867SMALL BUSINESS PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov4030 Moorpark Ave Suite 126San JoseCA95117-1801San JoseUS18MURA INC.4030 Moorpark Ave Suite 126San JoseCA95117-1801San JoseUS18The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project can lead to a revolution in 3D microgeometry and reflectance properties measurement of object surfaces at the micron-scale range. The proposed technology will significantly improve photorealistic rendering in digital prototyping, and therefore reduce the waste from using physical material samples during design, engineering, and manufacturing. This technology will help reduce product development time and cost, and lead to a greater sustainability.
The proposed project will develop a computational imaging system that allows for high-resolution 3D microgeometry and reflectance properties measurement of object surfaces. The current approaches for 3D surface measurement at the micron scale are based on sophisticated optical and mechanical components that are expensive and can be difficult to use, and most of these approaches cannot capture the full appearance of a surface, such as diffuse reflection, specular reflection, and surface roughness. The goal of this research program is to develop a combination of hardware and software that can measure 3D surface microgeometry and reflectance properties with micron-scale accuracy. The proposed technology is expected to achieve superior performance at greatly reduced cost.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CERILLO, LLCCerillo, LLCKevin P Seitter(434) 218-3151kevin@cerillo.net09/18/2018$748,389$748,38909/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Development of a Miniaturized Multiwell Plate Reader1831082080243584SMALL BUSINESS PHASE IIRuth M. Shuman(703) 292-2160rshuman@nsf.gov224A Shamrock RoadCharlottesvilleVA22903-3726CharlottesvilleUS05Cerillo, LLC100 2nd Street NW, Suite H1CharlottesvilleVA22902-5193CharlottesvilleUS05The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be an instrument that alleviates several current difficulties in the growth measurement of many microbes, especially anaerobic and other fastidious organisms. A large number of these species are naturally occurring in the human body, and have recently been shown to play critical roles in allergies, autoimmune diseases, dietary health, cancer, infection response, and more. The study of these species is considered by many to be the next frontier of modern medicine, especially as current approaches to managing infectious diseases, such as traditional antibiotics, appear to be losing effectiveness. However, current measurement technology is largely incompatible with the specialized environments and chambers in which anaerobic organisms must be grown. There is a large unmet need for better ways to measure anaerobic bacterial growth; this need is growing quickly as interest in the field increases. The ability to conduct high-throughput experiments in specialized environments will become critical as research into various human microbiomes accelerates, and demand for high-volume data grows. The existing market for high-throughput measurement devices is at least $300 million and growing. This platform will allow for systematic studies of cell culture growth that can be accomplished easily and economically.
This SBIR Phase II project proposes to develop and refine a miniaturized multi-well plate reader that measures optical characteristics of up to 96 cell samples for measuring growth of many microbial samples simultaneously. The continuing rise of systems and computational biology demonstrates a growing demand for large amounts of quantitative data, and the variety of microbes relevant to the human body necessitates such an approach. However, these measurement techniques are not universally accessible due to current instruments' complexity, size, and cost. This project will continue development of a miniature, simplified version of a device called a multi-well plate reader, expanding the availability of parallel growth measurement (and other metrics) to a wider array of researchers and environments. The first goal is to simplify the instrument's electronics, add an on-board display for clarity, and allow battery-powered operation. The next goal is to accelerate equilibration to any surrounding environment to allow proper functioning even in extreme conditions, by measuring a wide array of environmental variables at different points in space and time. The third goal is to solidify the device's mechanical aspects for reliability and stability in a shaker. Finally, this project will support the development of a fully-functional wireless interface for control and data management, allowing effective remote use in any environment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITYVirginia Polytechnic Institute and State UniversityKevin J Edgar(540) 231-0674kjedgar@vt.eduLynne S Taylor, Richard Daugherty09/18/2018$749,431$749,43109/15/201808/31/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITPFI-RP: Innovation of Materials Based on Sustainable Resources to Enhance Performance of Challenging Drugs and Drug Candidates.1827493003137015003133790PARTNRSHIPS FOR INNOVATION-PFIJesus Soriano Molla(703) 292-7795jsoriano@nsf.govSponsored Programs 0170BLACKSBURGVA24061-0001BlacksburgUS09Virginia Polytechnic Institute and State UniversityBlacksburgVA24061-0001BlacksburgUS09The broader impact/commercial potential of this PFI project is to enhance performance of the drugs that patients currently find on the pharmacist?s shelf, and to increase the number of effective new drugs that reach patients to treat critical medical issues. Currently up to 90% of drug candidates don?t fully dissolve in water, contributing to failure of otherwise effective candidates; all humans are roughly 70% water. We will design new materials, made from renewable resources and thus benign and environmentally sound, that solve key problems in drug delivery to patients. These currently unsolved problems include the inability to create patient-friendly formulations (pills) from drugs that require high doses (creating hard to swallow "horse pills"). Another important unsolved problem is failures of many drug candidates that tend to quickly form crystals from a water solution. When these drugs fail, cost of drug development goes up, which is ultimately passed along to patients. Drugs that would otherwise effectively treat diseases and are sorely needed by patients, never reach them. Our work will bring more drugs to patients, faster and more cheaply, and will reduce cost, side effects, dose, and variation in performance from patient to patient for drugs currently on the pharmacy shelf.
The proposed project targets the design, preparation, and evaluation of two new families of materials prepared from natural cellulose, which is incredibly abundant, renewable, benign, and harvested in large quantities already from trees. These materials will be carefully designed so as to be easily made by current manufacturers of cellulose derivatives, and to work exceptionally well at enhancing the performance of drugs. They will be designed to help create solutions of current drugs, or drug candidates that are under development, that have far more dissolved drug per volume than is possible using current technologies. The ability to create these more concentrated solutions of drug or drug candidates in the human body will permit patients to get enough drug/drug candidate into their bloodstream to have the desired therapeutic effect, but at much lower drug dose. We will design, make, and characterize these materials, show that they work to create more concentrated solutions of key drugs, and figure out what features enhance their performance, so we can design even better materials. With our industrial partners, we will advance the best candidate materials towards commercialization so that they can benefit patients.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.WOODS HOLE OCEANOGRAPHIC INSTITUTIONWoods Hole Oceanographic InstitutionJohn H Trowbridge(508) 289-2296jtrowbridge@whoi.eduAlbert J Plueddemann09/18/2018$220,000,000$10,662,90310/01/201809/30/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITManagement and Operation of the Ocean Observatories Initiative (OOI)1743430001766682001766682OCEAN OBSERVATORIES INITIATIVEBauke H. Houtman(703) 292-7704bhoutman@nsf.gov183 OYSTER POND ROADWOODS HOLEMA02543-1041Woods HoleUS09Woods Hole Oceanographic InstitutionMA02543-1041Woods HoleUS09The Ocean Observatories Initiative (OOI) is a research observatory with arrays of instrumented buoys, profilers, ocean gliders, and autonomous vehicles within different open-ocean and coastal regions, as well as a cabled array of instrumented platforms and profilers on and above the seafloor. This award to Woods Hole Oceanographic Institution (WHOI), for continued operations and management, builds upon the accomplishments of the initial OOI consortium, including cutting edge in-water infrastructure required to support transformative ocean observing. WHOI, the University of Washington (UW), Oregon State University (OSU), and Rutgers University (RU), will provide scientific and technical management and operation of OOI, beginning in 2018, for a five-year period with the possibility of a five-year extension. WHOI serves as the lead institution overall, as well as the marine implementing organization (MIO) for two global arrays, Irminger Sea in the North Atlantic, and Station Papa in the North Pacific, and one coastal array (referred to as the Pioneer Array), located on the East Coast of the U.S. UW will serve as the lead MIO for the Regional Cabled Array off the West Coast of the U.S., and OSU will serve as the lead for the second coastal array (the Endurance Array), located off the West Coast of the U.S. RU is responsible for the cyberinfrastructure and, in conjunction with the three MIOS, will focus on the data dissemination. A central portal for data access, supported by a common cyberinfrastructure, ties the system of systems together. The OOI can be used to investigate a spectrum of phenomena and processes including episodic, short-lived events, and more subtle, long-term changes in ocean systems, such as extreme events including storms, undersea volcanoes, and ocean circulation on continental shelfs and slopes. OOI data are vitally important for understanding ocean acidification, nutrient dynamics critical to fisheries, and other questions throughout the basic and applied science continuum of ocean sciences. As such, the OOI facility is providing the public, educators, students, and researchers with: (1) long-term time series data sets; (2) an in-situ ocean laboratory to allow users to submit proposals for development and application of new technologies by connecting their instruments or concepts to the OOI network; and (3) tools that will support undergraduate classroom applications of the OOI, as well as public outreach through informal education. The OOI delivers all data/metadata and education tools to the public via the internet at www.oceanobservatories.org.
The interdisciplinary OOI measurements provide comprehensive insight into the Earth, oceans and atmosphere, useful for scientists, educators, students, laypersons, industry, and policymakers. The Irminger Sea Array provides interdisciplinary measurements of the water column, mesoscale variability, and air-sea fluxes in a region of documented deep-water formation, which impacts the Atlantic meridional overturning circulation, a key component of the climate system. Together with ongoing NOAA measurements of air-sea fluxes, the OOI Array at Station Papa quantifies water column properties and mesoscale variability in a region of longstanding interdisciplinary interest. The Pioneer Array on the New England shelf break quantifies the interdisciplinary processes near the persistent shelf-slope front that drive some of the nation?s most productive ecosystems. The Regional Cabled Array, which brings high power and high-bandwidth, real-time, two-way communications into the oceans with adaptive sampling capabilities, provides new insights into interlinked seismic, volcanic, and hydrothermal processes operating off the Oregon coast, the flux of methane from the seafloor, the seafloor biosphere, high resolution temporal measurements of blue water and coastal ocean dynamics and ecosystems (e.g. hypoxia, thin layers, plumes), biogeochemical interactions, and turbulent mixing. The Endurance Array provides interdisciplinary observations within the coastal upwelling region of the Oregon and Washington coasts, providing synoptic, multi-scale observations of the greater eastern boundary current regime, and new insights into shelf/slope nutrient exchange, air-sea property exchange, carbon cycling, and ocean acidification. Taken together, OOI measurements improve understanding of processes impacting climate variability, ecosystems, fisheries, geohazards, and the subseafloor environment, which advance the capabilities of decision-makers charged with the wise stewardship of ocean resources.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKAUniversity of Nebraska-LincolnRezaul Mahmood(270) 745-5979rezaul.mahmood@wku.edu09/17/2018$287,636$184,60108/15/201808/31/2020GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: The Great Plains Irrigation Experiment (GRAINEX) for Understanding the Influence of Irrigation on the Planetary Boundary Layer and Weather Events1853390555456995068662618PHYSICAL & DYNAMIC METEOROLOGYNicholas F. Anderson(703) 292-4715nanderso@nsf.gov151 Prem S. Paul Research CenterLincolnNE68503-1435LincolnUS01University of Nebraska-LincolnLincolnNE68503-1435LincolnUS01This research project seeks to investigate the impacts of irrigation on the evolution of the planetary boundary layer atmosphere in a region of the Northern Great Plains, specifically in southeastern Nebraska. This study will determine the impacts of the rapid commencement of irrigation in the spring and resultant changes in the land-atmosphere (L-A) coupling at the mesoscale. Graduate students at Western Kentucky University and the University of Alabama at Huntsville will gain experience in studying/working with weather/climate models and gain field experience. These students will be guided by NCAR and NASA-GSFC experts also. Meanwhile, this project will also contribute science education to K-12 students in local middle schools. For land-atmospheric interaction and surface hydrology communities, the proposed work could potentially bring interesting findings to advance our understanding regarding the connection between local irrigation and precipitation.
The Southern Great Plain (SGP) is a "hot spot" where soil moisture plays an important role affecting the local atmospheric boundary layer processes and local cloud formation as well as precipitation. Land use change and irrigation due to agricultural activities could be important factors affecting local land-atmospheric interactions. This research will investigate the intra-seasonal changes in application in irrigation and their impacts on the boundary layer atmosphere and various processes and mechanisms involved in these changes. This study will collect field data in collaboration with the Lower Atmospheric Observation Facilities (LAOF) of the University Consortium for Atmospheric Research (UCAR) and conduct model simulations to further understand the impacts of irrigation on the atmosphere. To further understand land-atmosphere interactions and coupling, this study will use the Weather Research and Forecasting (WRF) model centered on southeastern Nebraska, a region containing strong soil moisture gradients due to widespread application of irrigation.UNIVERSITY OF MASSACHUSETTSUniversity of Massachusetts AmherstSeth W Donahue(970) 297-5050seth.donahue@colostate.edu09/17/2018$118,452$118,45109/01/201804/30/2019GrantNSF4900490047.074040100 NSF RESEARCH & RELATED ACTIVITEndocannabinoid Regulation of Bone Metabolism in Hibernating Marmots1854108153926712079520631Physiolg Mechansms&BiomechancsKathryn Dickson(703) 292-8413kdickson@nsf.govResearch Administration BuildingHadleyMA01035-9450HadleyUS02University of Massachusetts AmherstResearch Administration Building 100 Venture WayHadleyMA01035-9450HadleyUS02One of the goals of comparative physiology is to understand how different physiological systems impact each other. Endocannabinoids are signaling molecules derived from fatty acids that appeared early in evolution and play important roles in regulating numerous physiological processes including those that are altered in hibernation such as bone, fat, and energy metabolism. The research aims to understand how endocannabinoid signaling by fat cells affects bone remodeling in obese, but otherwise healthy hibernating marmots. The planned studies will provide research experiences for undergraduate students to prepare them for advanced education and careers in science. The educational outreach component of this award will help students understand how diet and exercise affect fat accumulation and overall health of organisms. It will also elucidate how some animals have evolved physiological systems that prevent disease during states of obesity and physical inactivity. It will develop an interactive exhibit for K-12 students to explore the differences between the metabolism and physical activity of a hibernating animal and themselves. It will develop research kits for middle school students to measure and understand the calorie content of specific foods. It will also develop a presentation on the unique physiological adaptations in hibernators to underserved K-5 students.
Hibernating mammals demonstrate remarkable resilience by having evolved physiological mechanisms that allow them to survive extreme physiological and environmental conditions for prolonged periods of time. Physical inactivity, obesity, and anorexia are well known to negatively impact bone metabolism and structure in non-hibernating animals. However, the physical inactivity, obesity, and anorexia that occur during hibernation do not negatively affect bone in marmots. The research will investigate the role of the endocannabinoid system in preventing bone loss in hibernating marmots. The research will test the general hypothesis that the endocannabinoid system regulates bone metabolism during hibernation to prevent bone loss. The project will undertake an interdisciplinary approach to understanding the role of paracrine signaling from bone marrow adipocytes in endocannabinoid regulated bone metabolism during hibernation. Novel targeted mass spectrometry methodology to measure tissue levels of endocannabinoid ligands, with greater sensitivity than previously reported, will be used to measure endocannabinoid levels in marmot serum, bone, and adipose tissue. Pharmacological blocking will be used to assess the role of specific components of the endocannabinoid system in regulating bone remodeling and structure during hibernation. Additionally, the methodology and results from the study will provide the conceptual framework for modeling how the endocannabinoid system regulates metabolism in other physiological systems during the extreme conditions of hibernation.AMERICAN SOCIETY FOR ENGINEERING EDUCATIONAmerican Society For Engineering EducationDamon L Tull(202) 331-3500d.tull@asee.org09/17/2018$5,324,970$5,324,97010/01/201808/31/2022GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITInnovative Postdoctoral Entrepreneurial Research Fellowship (I-PERF)1853888020293395020293395SBIR Outreach & Tech. AssistJesus Soriano Molla(703) 292-7795jsoriano@nsf.gov1818 N ST NW STE 600WASHINGTONDC20036-2476WashingtonUS00American Society For Engineering EducationDC20036-2479WashingtonUS00The broader impact of the proposed postdoctoral fellowship program will be an increase in the number of persons from underrepresented groups such as women, African Americans, Hispanic Americans, American Indians, and Hawaiian/Pacific Islanders and those with disabilities who perform small business research in support of the federal government and participate in technology development and entrepreneurship in the private sector. This program is aimed at defining a new career pathway for entrepreneurial-minded, underrepresented scholars. It is proposed that the policies, planned interactions with program managers, entrepreneurs and investors, professional development programming, and the overall opportunity provided will succeed in this effort where other efforts have come short. In addition, the program will actively engage underrepresented groups and innovative start-up and small business companies in geographically under-served states as defined by National Science Foundation (NSF) Established Program to Stimulate Competitive Research (EPSCoR).
The proposed postdoctoral fellowship program will create new professional development opportunities for underrepresented fellows in qualified innovative start-up companies and small business that receive SBIR/STTR Phase II funding from NSF. On the long term, the program is expected to expand the participation of underrepresented innovators in the US innovation ecosystem, through the creation of new technology jobs and more start-up companies.
In FY 2013, the last year data was available to the proposing team, the Small Business Administration (SBA) made 5,159 Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) Phase I and Phase II awards totaling $2.1 billion. Only 236 or 4.57% awards were made to minority owned firms that year. For comparison, this outcome is lower than the percent and number of Science and Engineering (S&E) doctorates awarded to under-represented groups that year, 12.64% and 2,897 respectively, and does not reflect the capacity of the more than 130,000 underrepresented S&E doctorate degree holders in the U.S. workforce. A similar problem is found in the private sector. In 2016, venture capitalists invested $58.2 billion in 5,839 male-founded companies compared to just $1.46 billion in 359 female-founded companies; women represented 4.94% of the deal flow. The percentages are lower among minority business enterprises. The proposed postdoctoral fellowship program will directly address the aforementioned challenges at a time in the 21st century where the primacy of United States (US) innovation is facing unprecedented competitive pressure.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNAVCO, INCUNAVCO, Inc.Meghan Miller(303) 381-7514Meghan@unavco.orgCharles M Meertens, Glen S Mattioli, Donna Charlevoix09/17/2018$763,842$763,84209/01/201808/31/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth Ssystem Dynamics: Geodetic Facility for the Advancement of Geoscience (GAGE)-NASA Scope1851169142357032GAGERussell C. Kelz(703) 292-4747rkelz@nsf.gov6350 Nautilus Dr.BoulderCO80301-5394BoulderUS02UNAVCO6350 Nautilus DriveBoulderCO80301-5394BoulderUS02UNAVCO will develop, operate, and maintain a distributed, multi-user Geodetic Facility for the Advancement of GEoscience (GAGE). Geodesy characterizes the Earth's time varying shape, orientation in space, mass distribution, and gravity field. It has revolutionized the geosciences, by measuring Earth changes with unprecedented spatial and temporal resolution. The GAGE facility employs expert professional staff, with guidance provided by the scientific community, to manage and operate a set of foundational geodetic capabilities that are essential for current research support, as well as frontier geodetic activities that will enable future research. The facility will promote advances in our understanding of continental deformation; tectonic plate boundary processes; the processes that drive earthquakes, volcanic eruptions and landslide hazards; continental water storage, atmospheric, ice sheet and glacier dynamics; and interactions among these components of the Earth system. The geodetic capabilities provided through the GAGE facility contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data products from GAGE will be used by federal agencies including the National Aeronautics and Space Administration, the United States Geological Survey and the National Oceanic and Atmospheric Administration, for missions including spacecraft positioning, satellite orbit, and timing corrections; earthquake, tsunami, and volcano early warning; weather forecasting; water resources; and environmental management. State departments of transportation will use GAGE data to help support traffic monitoring and control and increasingly GAGE data will support commercial sector positioning needs including for agriculture, construction and surveying, transportation (including air, rail, and maritime), mining and resource exploration, and fleet vehicle tracking.
The GAGE facility will manage and operate: 1) global and regional continuously operating Global Navigational Satellite Systems (GNSS) and complementary geodetic technology networks; 2) portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) geodetic instrumentation testing and support service; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs that foster the development of the next generation geosciences workforce, are designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences, and engage the public by highlighting advances in geophysical sciences and their societal relevance. Innovative and transformative research that will benefit from GAGE examines both the dynamics of individual processes and the nonlinear interactions within and among larger Earth systems. The study of active processes from geocenter motion to the studies of the lithosphere, cryosphere, hydrosphere, and atmosphere requires understanding of the coupling and feedbacks across a range of length and time scales, and between the solid Earth and its fluid envelopes, in both physical and biological environments. Under NSF, and NASA partner agency support for GAGE, UNAVCO will integrate and federate a set of currently operated but at present independently managed GNSS stations to form the Network of the Americas (NOTA). UNAVCO will modernize NOTA stations with state-of-the-art, multi-sensor, multi-GNSS, receivers with real-time streaming data and analysis. These enhancements will enable higher precision positioning than currently possible and new application of GNSS data that can be used for geohazards warning systems, study of ocean and atmosphere dynamical behavior, and observation of key environmental parameters such as water storage, soil moisture, and sea and lake-level changes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF BOSTON UNIVERSITYTrustees of Boston UniversityMilos A Popovic(617) 358-6188mpopovic@bu.eduPrem Kumar, Vladimir M Stojanovic09/17/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: Single-Chip, Wall-Plug Photon Pair Source and CMOS Quantum Systems on Chip1842692049435266049435266COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov881 COMMONWEALTH AVEBOSTONMA02215-1300BostonUS07Trustees of Boston University8 Saint Mary's StreetBostonMA02215-1300BostonUS07The amount of new data generated by humanity in the past year exceeds that created in all of human history before. The processing demands of this data are driving the continued need for greater computational power, in domains including big data analytics, artificial intelligence, and augmented reality, serving technologies including personal, medical, research, engineering, finance, and weather prediction. As "Moore's Law" of the semiconductor industry - which has guaranteed continued advance of computing power in the last 50 years - has ground to a halt in the past decade, new computational paradigms are being sought to remedy this dire situation. Quantum information technology is the new and ultimate frontier for signal processing and computing and leverages the unintuitive laws of our universe that hold on small scales. 50-100 qubit processors have been developed by Intel, IBM and Google, but quantum optical networks, needed to network them into "quantum data centers" in a way similar to their conventional analogues, are missing. This project aims to fill that gap by developing a new electronic-photonic chip technology and framework to allow creation of electronic-photonic quantum systems-on-chip (epQSoCs). epQSoCs combine light, electronic circuits, and quantum functions on a single microchip that can provide a widely deployable technology platform for quantum networks. The project will combine interdisciplinary expertise in photonics, electronic systems, and quantum communications to demonstrate the first epQSoC. A single-chip, "wall-plug" source of quantum correlated photon pairs, this epQSoC is a fundamental building block for more complex epQSoCs and for quantum networks. By integrating several components and novel capabilities never previously integrated in a single chip, this source will provide new levels of photon-pair source performance. The interdisciplinary project team will also educate a new generation of engineers in this emerging new technology area to foster innovation, excellence and global leadership in the United States.
A "wall plug" single-chip source of photon pairs, a fundamental building block of most quantum photonic systems, will be demonstrated having a high efficiency, rate and reconfigurability to produce factorizable quantum states and allow heralding of pure single photons. No such integrated device exists despite the fact that a rack-mounted fiber-nonlinearity-based source of this kind for lab use has been commercialized for almost a decade. The proposed project aims to change the quantum technology landscape with the demonstration of a fully integrated single-chip quantum pair source system. The chip photonic circuit will contain photonic elements for pre- and post-source linear pump filtering, a resonant nonlinear pair generator, pump pulse carver to allow active matching of the pump pulse length to the source's resonant bandwidth in order to control the produced photons joint spectral intensity (to yield a factorizable or other engineered biphoton states), and an ultra-low loss interface to fiber. The proposed approach addresses a number of challenges that arise in integration, on-chip filtering, and real-time control. In addition to standalone operation, the pair source will be the first implementation of an electronic-photonic quantum system-on-chip (epQSoC) and a key building block for more complex integrated quantum systems. The proposed epQSoCs will be implemented in a commercial 45nm CMOS electronic-photonic platform (with potential for integrating single-photon detectors on chip as well).
The project will create the technology framework (block libraries, tools, models and design methodologies) for low-cost, rapid innovation and design of sophisticated epQSoCs. This framework, along with associated educational materials and experiences will help create a new crop of engineers that are capable of tackling the complex, multidisciplinary nature of quantum information systems. Educational and outreach activities will provide exposure and training to a new generation of students and future leaders in this field, with special focus on underrepresented students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF ARIZONAUniversity of ArizonaSaikat Guha(520) 621-7595saikat@email.arizona.eduDaniel Kilper, Linran Fan09/17/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: Quantum repeater for long-distance quantum communication enabled by non-Gaussian cluster states on a scalable hybrid aluminum nitride and silicon nanophotonic platform1842559806345617072459266COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov888 N Euclid AveTucsonAZ85719-4824TucsonUS03University of Arizona1630 E University BlvdTucsonAZ85721-0094TucsonUS03RAISE-EQuIP: Quantum repeater for long-distance quantum communication enabled by non-Gaussian cluster states on a scalable hybrid aluminum nitride and silicon nanophotonic platform
Saikat Guha, Linran Fan, Dan Kilper, University of Arizona
Principles from quantum physics will enable far superior computational capabilities, better sensors and secure communications that are provably unbreakable by any adversary. Most of these advancements will be enabled by a new information resource called quantum entanglement. One of the most important building blocks to realize a quantum-enabled network information infrastructure that is capable of generating and distributing entanglement at high rates over long distances is the quantum repeater a quantum enabled processor that will sit at the node of the future quantum internet, augmenting the current-day network router. Our project?s goal is to research, develop and test a design for the quantum repeater, which will be realized compactly in an integrated photonic platform that produces complex many-photon entangled states on demand. The successful completion of this project will enable various applications of shared entanglement, including future-proof secure communications and multi-party secure computations, entanglement-assisted distributed sensors for far superior imaging and remote sensing, and will enable new science discoveries in areas such as chemistry and high-energy physics by letting us experiment with entangled states larger than any created so far. Even though our main thrust is to research a scalable on-chip design of a quantum repeater, the theoretical work will help us develop a deep understanding of building general and special-purpose quantum processors that use photons to encode the qubit, whereas the versatile nanophotonic platform we will design will be of value to various quantum enabled photonic information processing with applications to distributed sensing and distributed cloud-based quantum computing. Because of the highly-interdisciplinary nature of quantum information science, and our project team in particular, our education and outreach program will have a particularly broad impact in training a diverse and strong workforce at the intersection of physics, optical sciences, electrical and material science and engineering, computer network theory, and mathematics.
The biggest challenge in building a quantum repeater has been the lack of good-quality quantum memories, high-rate good-fidelity matter-photon entanglement sources, and high-efficiency quantum-state-preserving frequency interconversion so as to make a telecom-wavelength quantum photon be compatible with the quantum storage and processing units. Our project?s goal is to research and develop a design of a quantum repeater that does not need quantum memories or quantum interconversion, but uses an integrated photonic source of locally-generated complex entangled states of many photonic modes to replace the action of the quantum memory by providing virtual storage of a logical quantum bit (qubit) using quantum error correction against photon loss. Such repeaters, known as all-photonic repeaters, have been proposed and recently researched by members of our team. But existing work on such repeaters need millions of near-perfect single-photon sources and detectors, along with extremely low-loss linear-optical waveguides be supplied at each repeater node. Our key insight is to develop an alternative scheme that leverages recently-demonstrated photonic multi-mode-squeezed entangled states of thousands of modes as the cluster source, but built compactly on a hybrid Aluminum Nitride - Silicon photonic platform, and use photon number detection on a subset of those modes to cast that into a universal-quantum-capable coded cluster state and develop a new logical qubit encoding into that "non-Gaussian" cluster state in a so-called Schrodinger-cat-like qubit basis. The goals of this project are: (1) establishing the theoretical design principles of a technologically-feasible all-photonic quantum repeater based on a continuous-variable (CV) entangled cluster source, (2) developing a compact, versatile integrated nanophotonic platform for generating and manipulating CV cluster states, (3) realizing direct on-demand generation of non-Gaussian universal clusters at high rates, and (4) the first measurement of entanglement distribution over one quantum repeater link that exceeds the fundamental direct-transmission rate upper limit for entanglement generation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BROWN UNIVERSITY IN PROVIDENCE IN THE STATE OF RHODE ISLAND AND PROVIDENCE PLANTATIONSBrown UniversityDaniel Mittleman(401) 863-1425daniel_mittleman@brown.edu09/17/2018$200,000$200,00010/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Terabit DSL1842023001785542001785542COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govBOX 1929ProvidenceRI02912-9002ProvidenceUS01Brown University182 Hope StreetProvidenceRI02912-9037ProvidenceUS01EAGER: Transmitting data at a terabit per second on twisted copper wires
The transmission of data using twisted copper-wire pairs was pioneered by Alexander Graham Bell in 1881. Today, there are well over a billion such twisted pairs installed globally, an infrastructure which has been the basis for nearly all telephone connections for over 100 years. In the late 1980s Digital Subscriber Line (DSL) services were developed, in which an RF signal carrying digital data was essentially piggy-backed on top of the same copper wires used for analog voice signals. Through advances in data encoding and frequency multiplexing, these systems can now typically deliver data at gigabit per second rates. The astounding (and ongoing) commercial success of DSL arises largely from the fact that these services do not require new wire or fiber connections (which cost thousands of dollars per customer to install), but instead can deliver high bit rates to customers using the existing infrastructure. However, advances in encoding and multiplexing have nearly reached their limit, so the only way to further increase the data rate is to increase the frequency of the RF carrier wave, since there is more bandwidth available at higher frequencies. The proposed research will explore the use of these existing copper twisted-cables for transmission of signals at much higher frequencies than those that have previously been employed in DSL systems. Similar multiplexing and encoding schemes will be necessary, due to the unavoidable mixing of these high-frequency signals as they propagate along these non-uniform cables. If these signal processing approaches are still useful at high frequencies, and if the overall signal loss is not too high, then this initial demonstration will validate the feasibility of operating a DSL-like system with a data rate of a terabit per second, vastly higher than anything that has been envisioned previously. This would open up an entirely new realm for fixed (not wireless) data services.
This EAGER proposal suggests a radically new way to think about DSL transmission systems. In all discussions to date, the fundamental physics of the electromagnetic signal propagation is described using the language of transmission lines. Conventionally, a transmission line guides an electrical signal by propagation of a time-varying voltage between a pair of electrically isolated conductors. However, when the free-space wavelength of the guided wave approaches the relevant dimensions (e.g., the distance between the two conductors), it is more appropriate to describe this transmission process using the language of waveguides. Inspired by the fact that the typical free-space distance between wires in a twisted-wire pair can be on the order of a millimeter, this project seeks to study the use of millimeter waves or terahertz waves as the carriers for modulated digital data on twisted-pair cables, acting as waveguides. This proposal seeks to initiate a research collaboration between the PI at Brown University and engineers at ASSIA, Inc. This company specializes in the software and signal processing that enables efficient use of spectrum in DSL systems. Their expertise, in particular in the area of vectoring (conceptually equivalent to MIMO in wireless systems), combined with the PI's expertise in millimeter-wave and terahertz waveguides, represents a unique team which is ideally positioned to carry out the proposed exploratory research program. The approach involves the experimental characterization of the waveguide modes (all output modes for each possible input excitation) for a set of model cable systems, starting from a simple single-twisted-pair and working up to more complicated (and longer) waveguides. The effects of modal dispersion, dielectric loss, and bends will be studied, and the results will be used as inputs in channel models developed by ASSIA to predict the rate and range performance characteristics. This work represents the first realistic exploration of the idea of using millimeter waves for long-distance guided-wave data transmission.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VANDERBILT UNIVERSITY, THEVanderbilt UniversityJanos Sztipanovits(615) 322-3455Janos.Sztipanovits@Vanderbilt.eduFrankie King09/17/2018$214,849$214,84910/01/201809/30/2019GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVIT2018 CPS PI Meeting1840713965717143004413456CYBER-PHYSICAL SYSTEMS (CPS)David Corman(703) 292-8950dcorman@nsf.govSponsored Programs AdministratioNashvilleTN37235-0002NashvilleUS05Vanderbilt University1025 16th Avenue South Suite 102NashvilleTN37212-2328NashvilleUS05The purpose of this project is to plan and organize the 2018 National Science Foundation (NSF) Cyber-Physical Systems (CPS) Principal Investigator (PI) Meeting. This meeting convenes all PIs of the NSF CPS Program for the ninth time since the program began. The PI Meeting is to take place on November 15-16, 2018 in Alexandria, Virginia. The PI meeting is an annual opportunity for NSF-sponsored CPS researchers, industry representatives, and Federal agency representatives to gather and review new CPS developments, identify new and emerging applications, and to discuss technology gaps and barriers. The program agenda is community-driven and includes presentations (oral and poster) from PIs, reports of past year program activities, and showcase/pitch new CPS innovations and results.
The annual PI Meeting serves as the only opportunity where the NSF funded CPS Principal Investigators meet to share their research, discuss new research opportunities and challenges, and explore new ideas and partnerships for future work. Furthermore, the PI meeting is also an opportunity for the academic research community to interact with industry entities and government agencies with vested interest in CPS research and development. The PI Meeting is a forum for sharing ideas across the CPS community. It has played a major role in growing the community across a broad range of sectors and technologies, and performing outreach to others who have interest in learning about the program and participating as future proposers, transition partners, or sponsors. The 2018 PI meeting will feature lightning talks from researchers, poster sessions, special topic workshops, demonstrations and keynotes from leaders in the research community.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TEXAS A&M ENGINEERING EXPERIMENT STATIONTexas A&M Engineering Experiment StationNicholas Duffield(979) 845-7328duffieldng@tamu.eduKrishna Narayanan, Srinivas Shakkottai, Alireza Talebpour09/17/2018$300,000$300,00010/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Learning-Mediated Control for Traffic Shaping1839816847205572847205572COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govTEES State Headquarters Bldg.College StationTX77845-4645College StationUS17Texas A&M Engineering Experiment StationCollege StationTX77845-4645College StationUS17Efficient Management of Vehicular Traffic via Real-time Machine-Learning-Mediated Control and Traffic Shaping
While connectivity and automation promise orders of magnitude gains in the safety and efficiency of vehicular transportation networks, these gains cannot be realized without monitoring, learning the behavior, and control of vehicles at different aggregation levels. Indeed, current congestion mitigation methods, such as speed harmonization that uses a sequence of variable speed limits along a highway do not reliably control congestion, and may exacerbate it (e.g., via shocks propagated through speed limit changes) due to the inconsistency between congestion prediction and real-time control. The objective of this project is to develop a holistic approach using machine-learning methods to identify and predict macroscopic congestion behavior of traffic based on both vehicle-borne and transportation infrastructure measurements, while designing fine-grain control systems for individual vehicles that can help to mitigate congestion effects. In doing so, the project recognizes that these designs must account for the possibility of low take-up rates of connected, automated vehicles (CAVs) over the next decade, and the consequent dominance of human-mediated vehicle operation for some time to come. The project also includes the development of educational materials on data analytics and vehicular control systems. Intrinsic to the program are efforts at outreach to involve high-school students via demonstrations and lectures based on the technology developed.
The goal of this project is to develop the theory of and evaluate a novel approach to traffic management entitled "real-time learning-mediated control". The key idea is to meld large-scale real-time learning about macroscopic phenomena in a physically interpretable manner, with distributed dynamic control of individual vehicles in a provably safe and efficient manner. The work comprises two thrusts, namely (i) Traffic State Prediction, which offers a Graph Signal Processing (GSP)-based congestion prediction approach for planned and unplanned congestion-causing events, and (ii) Traffic Shaping and Control, which offers novel vehicular control methods that shape traffic in a stable manner over the multiple dimensions of target time headway and velocities over space and time, and candidate time-gap and velocity profiles in a mixed environment of both connected, automated vehicles and human driven ones. Thus, the overall aim is to combine the ability of learning methods to provide predictions about complex interconnected systems, with control laws that are safe and consistent with the laws of physics. The value of this research to broader society is in combining traffic prediction, control and learning, which can result in accurate congestion mitigation and increased throughput. Incorporating analytical concepts into senior design projects and courses enhances the project via educational impact. The project also contributes to development of systems-design expertise for students, as well as to diversity enhancement through minority student engagement.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MISSOURI SYSTEMMissouri University of Science and TechnologyBruce M McMillin(573) 341-6435ff@mst.eduJonathan Kimball, Zhishan Guo, Rui Bo09/17/2018$962,695$962,69510/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted Components1837472804883767006326904CYBER-PHYSICAL SYSTEMS (CPS)Phillip Regalia(703) 292-8910pregalia@nsf.gov300 W 12th StreetRollaMO65409-6506RollaUS08Missouri University of Science and Technology300 W 12th StreetRollaMO65409-6506RollaUS08The nation's critical infrastructures are increasingly dependent on systems that use computers to control vital physical components, including water supplies, the electric grid, airline systems, and medical devices. These are all examples of Cyber-Physical Systems (CPS) that are vulnerable to attack through their computer systems, through their physical properties such as power flow, water flow, chemistry, etc., or through both. The potential consequences of such compromised systems include financial disaster, civil disorder, even the loss of life. The proposed work significantly advances the science of protecting CPS by ensuring that the systems "do what they are supposed to do" despite an attacker trying to make them fail or do harm. In this convergent approach, the key is to tell the CPS how it is supposed to behave and build in defenses that make sure each component behaves and works well with others. The proposed work has a clear transition to industrial practice. It will also enhance education and opportunity by opening up securing society as a fascinating discipline for K-12 students to follow.
The objective of the proposed project is to produce, from untrusted components, a trusted Cyber-physical system (CPS) that is resilient to security attacks and failures. The approach will rely on information flows in both the cyber and physical subsystems, and will be validated experimentally on high fidelity water treatment and electric power CPS testbeds. The project brings together concepts from distributed computing, control theory, machine learning, and estimation theory to synthesize a complete mitigation of the security and operational threats to a CPS. The proposed method's key difference from current methods is that security holes will be identified and plugged automatically at system design time, then enforced during runtime without relying solely on secure boundaries or firewalls. The system will feature the ability to identify and isolate a malfunctioning device or cyber-physical intrusion in real-time by validating its operation against fundamental scientific/engineering principles and learned behavior. A combined mathematical/data science approach will be used to generate governing invariants that are enforced at system runtime. Invariants are a scientific approach grounded in the system's physics coupled with machine learning and real-time scheduling approaches embedded in the CPS. Robust state estimation will account for errors in measurement and automated security domain construction and optimization to reduce the cost of evaluation without sacrificing coverage. The successful outcome of this research will lead to improved national security across various CPS infrastructures which, in turn, will improve economic and population health and security. The work can be taken to industry for deployment in critical infrastructures. The project will stimulate interest in Science, Technology, Engineering and Mathematics (STEM) through the development of a water-themed tabletop exercise for K-12 and helping current college students develop an interest in outreach through the experiential learning aspects of developing the tabletop exercise.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PURDUE UNIVERSITYPurdue UniversityAditya P Mathur(765) 494-7823apm@cs.purdue.edu09/17/2018$37,200$37,20010/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: TTP Option: Medium: Collaborative Research: Trusted CPS from Untrusted Components1837352072051394072051394CYBER-PHYSICAL SYSTEMS (CPS)Phillip Regalia(703) 292-8910pregalia@nsf.govYoung HallWest LafayetteIN47907-2114West LafayetteUS04Purdue University155 South Grant StreetWest LafayetteIN47907-2114West LafayetteUS04The nation's critical infrastructures are increasingly dependent on systems that use computers to control vital physical components, including water supplies, the electric grid, airline systems, and medical devices. These are all examples of Cyber-Physical Systems (CPS) that are vulnerable to attack through their computer systems, through their physical properties such as power flow, water flow, chemistry, etc., or through both. The potential consequences of such compromised systems include financial disaster, civil disorder, even the loss of life. The proposed work significantly advances the science of protecting CPS by ensuring that the systems "do what they are supposed to do" despite an attacker trying to make them fail or do harm. In this convergent approach, the key is to tell the CPS how it is supposed to behave and build in defenses that make sure each component behaves and works well with others. The proposed work has a clear transition to industrial practice. It will also enhance education and opportunity by opening up securing society as a fascinating discipline for K-12 students to follow.
The objective of the proposed project is to produce, from untrusted components, a trusted Cyber-physical system (CPS) that is resilient to security attacks and failures. The approach will rely on information flows in both the cyber and physical subsystems, and will be validated experimentally on high fidelity water treatment and electric power CPS testbeds. The project brings together concepts from distributed computing, control theory, machine learning, and estimation theory to synthesize a complete mitigation of the security and operational threats to a CPS. The proposed method's key difference from current methods is that security holes will be identified and plugged automatically at system design time, then enforced during runtime without relying solely on secure boundaries or firewalls. The system will feature the ability to identify and isolate a malfunctioning device or cyber-physical intrusion in real-time by validating its operation against fundamental scientific/engineering principles and learned behavior. A combined mathematical/data science approach will be used to generate governing invariants that are enforced at system runtime. Invariants are a scientific approach grounded in the system's physics coupled with machine learning and real-time scheduling approaches embedded in the CPS. Robust state estimation will account for errors in measurement and automated security domain construction and optimization to reduce the cost of evaluation without sacrificing coverage. The successful outcome of this research will lead to improved national security across various CPS infrastructures which, in turn, will improve economic and population health and security. The work can be taken to industry for deployment in critical infrastructures. The project will stimulate interest in Science, Technology, Engineering and Mathematics (STEM) through the development of a water-themed tabletop exercise for K-12 and helping current college students develop an interest in outreach through the experiential learning aspects of developing the tabletop exercise.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF DARTMOUTH COLLEGEDartmouth CollegeDavid F Kotz(603) 646-1439David.F.Kotz@Dartmouth.eduKofi Odame, Ryan Halter, Xing-Dong Yang09/17/2018$976,098$408,58610/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITABR: Collaborative research: Smart earpiece for supporting healthy eating behaviors1835983041027822041027822Computer Systems Research (CSRM. Mimi McClure(703) 292-5197mmcclure@nsf.govOFFICE OF SPONSORED PROJECTSHANOVERNH03755-1404HanoverUS02Dartmouth College6211 Sudikoff LabHanoverNH03755-3510HanoverUS02Obesity is one of the most pressing health challenges faced by our country, and has been the target of much attention in the mobile health (mHealth) community. While the science of obesity indicates that diet is a major factor in healthy weight management, scientists are still not able to effectively, quickly and easily measure eating behavior. This project's goal is to develop a digital earpiece comfortable enough to wear (on or near the ear) that can sense and detect eating behavior. The project's long-term vision is to enable health researchers to better understand eating-related behaviors and, subsequently, to support the development of effective interventions that promote healthy diet and behavior.
Ultimately, a better understanding of eating-related behaviors, and better design of effective interventions regarding eating behavior, will have profound impact on personal and public health as well as the national economy. The project's hardware and software prototypes will be shared widely in the research community to enable experimentation around the sensing and interaction opportunities possible in an earpiece device. Furthermore, the project directly involves undergraduate and graduate students in interdisciplinary research, and outreach to middle-school students, expanding the supply of scientists educated in this important emerging topic.
The project will build a prototype wireless earpiece, with low-power (microwatt-scale) electronics and software sufficient to allow for the battery to last a full waking day; to develop efficient algorithms for detecting and distinguishing health-related behaviors; and to develop easy and effective means for the wearer to interact with the earpiece and its applications.
The team expects to answer scientific questions important to achieving the above goals. Specifically, they seek to advance scientific knowledge through the design and development of a wireless earpiece capable of sensing behavior and interacting with its wearer; develop novel low-power analog electronics and distributed software algorithms for inferring relevant behaviors from sensor data; develop novel interaction modalities involving bone-conduction audio between the earpiece and its wearer, complemented by tactile interfaces on the earpiece, on the skin, or on auxiliary devices like a wristband or smartphone; and validate these approaches through user studies and experiments inside and outside the lab.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF WISCONSIN SYSTEMUniversity of Wisconsin-MadisonLawrence Landweber(608) 263-7442lhl@cs.wisc.edu09/17/2018$299,972$299,97210/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITMERIF: A Forum for CISE-supported Midscale Experimental Research Infrastructure projects Projects1834880161202122041188822CISE RESEARCH RESOURCESJohn Brassil(703) 292-8950jbrassil@nsf.gov21 North Park StreetMADISONWI53715-1218MadisonUS02University of Wisconsin-Madison1210 W. Dayton St.MadisonWI53706-1613MadisonUS02The computer and networking systems research communities recognize the importance of conducting verifiable, repeatable experimental research at scale on highly decentralized Midscale Experimental Research Infrastructures (MERI). In the past decade the Directorate for Computer & Information Science & Engineering (CISE) has supported multiple research infrastructure projects, including the Global Environment for Network Investigations (GENI), and NSF Future Cloud projects including CloudLab and ChameleonCloud. The potential of MERI projects to support transformative research grows as experiments are envisioned that span multiple infrastructures providing complementary services. These experiments place new demands on each infrastructure to coordinate development and implement common protocols and interfaces to support interoperability and ease-of-use by experimenters.
This project seeks to create a community-led research coordination entity known as the MERI Forum (MERIF) to help achieve these objectives. MERIF will convene the CISE research infrastructure development community, experimenters, and other key stakeholders to communicate, cooperate and collaborate on MERI development. The project embarks with 6 primary responsibilities:
1. Advancing the Federation and Harmonization of MERIF projects to enable and simplify their use;
2. supporting Education and Outreach to integrate the use of the diversity of MERIF project resources in academic courses, including use by underserved populations;
3. hosting workshops to focus on midscale infrastructure solutions for a future national computation fabric that enables research experimentation into future networking and computing architectures;
4. convening regular research community meetings to identify the needs of MERI research users;
5. reaching out to domain science communities to identity and initiate mutually beneficial collaborations between MERI projects and large-scale science and engineering projects; and
6. engaging university Leadership to increase awareness and help sustain MERIF projects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ALLAN HANCOCK JOINT COMMUNITY COLLEGE DISTRICTAllan Hancock CollegeDominic J Dal Bello(805) 922-6966ddalbello@hancockcollege.edu09/17/2018$1,224,182$1,224,18210/01/201809/30/2023GrantNSF4900490047.076045176 H-1B FUND, EHR, NSFCollaborative Research - Enabling Transfer Students Access to Engineering1834154620874305620874305S-STEM:SCHLR SCI TECH ENG&MATHAlexandra Medina-Borja(703) 292-7557amedinab@nsf.gov800 South College DriveSanta MariaCA93454-6399Santa MariaUS24Allan Hancock College800 S. College DriveSanta MariaCA93454-6399Santa MariaUS24The NSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program supports the retention and graduation of high-achieving, low-income students with demonstrated financial need. This project, at Allan Hancock College, Cuesta College, and California Polytechnic State University (Cal Poly) will fund fifty 2-year scholarships at Allan Hancock and fifty 2-year scholarships at Cuesta College in cohorts of 25 students who are pursuing transfer to a B.S.-granting institution in engineering. In addition, this project will fund sixty-two scholarships at Cal Poly for transfer students from Allan Hancock and Cuesta, thus providing support to the students until their graduation with a B.S. degree in engineering. Allan Hancock and Cuesta are highly-ranked Hispanic-Serving Institutions. Cal Poly is one of only five comprehensive polytechnic universities in the nation, ranked as a one of the nation?s top public masters-level institutions. This project will build on and strengthen collaborative efforts to increase the number of low-income students who begin their engineering education at Allan Hancock or Cuesta, transfer to Cal Poly, are retained in, and graduate with a B.S. degree, and enter a STEM graduate program or the STEM workforce.
Specific program activities seek to remove or minimize economic barriers and support student development in five areas: 1) academic; 2) engineering transfer/career path; 3) personal, via Strengths and Growth Mindset training from a Social Justice perspective; 4) connection; and 5) professional. The project will also adopt essential evidence-based transfer practices, continuously assessing progress achieved in this area within and across each participating campus to institutionalize more robust transfer pathways and support the success of all future STEM transfer students at Allan Hancock, Cuesta, and Cal Poly. The project will include two research strands designed to advance understanding of strategies that enhance transfer student success in a career in engineering. The first research project will use social network analysis, survey methods, and qualitative interviews to advance understanding of how project activities contribute to a) growth of student social networks; b) increase in student resilience, confidence, sense of community, and sense of belonging; and c) whether growth in these areas is related to increased student retention, pre-transfer success, transfer, and post-transfer success. The second research project will integrate pre- and post-transfer Scholars into existing research to advance understanding of student motivations and perceptions when choosing to participate in (or leave) co-curricular team projects in engineering. The integration of Scholars allows for investigation of whether decision-making factors regarding participation in co-curricular team projects are consistent for student groups at community colleges and four-year institutions, and for students who are directly admitted or transfer to a 4-yearinstitution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.KW ASSOCIATES LLCKW Associates LLCPaul E King(503) 939-3571paul@amperescientific.com09/17/2018$704,537$704,53709/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Vacuum Arc Control using Arc Position Sensing and Induced Magnetic Fields1831255035221834SMALL BUSINESS PHASE IIBen Schrag(703) 292-8323bschrag@nsf.gov33900 Eastgate Circle SECorvallisOR97330-2256CorvallisUS04KW Associates LLC33827 SE Eastgate CircleCorvallisOR97333-2026CorvallisUS04This Small Business Innovation Research (SBIR) Phase II project will provide commercial validation at scale of feedback-based control of arc behavior within the vacuum arc remelting (VAR) process. This will improve VAR performance in the production of specialty metals, resulting in improvements to ingot quality while reducing electricity consumption. Specialty metals, such as titanium and nickel alloys, are used in critical high-performance parts in industries such as aerospace, energy, and medicine, where the failure of these parts may lead to catastrophic systems failures and potentially life-threatening situations. In a VAR furnace, extreme temperature gradients from constricted and/or diffuse arcs sustained between the melting electrode and ingot can cause non-homogeneous material and inclusion defects, resulting in up to 8% yield loss per ingot, representing $1.024 billion in losses across the domestic industry. Improved control over the arc distributions during the melting of these metals is expected to decrease the frequency of defects in the final product and increase overall yield from the process. The proposed project is expected to reduce these loses by up to 50% through the application of active, feedback control of the arc dynamics. This type of control is expected to increase yield, decrease energy requirements, and increase safety of the manufacturing process industry-wide.
This project will result in a system capable of detecting and manipulating the distribution of the arcs utilized during VAR processing. The Phase I effort showed that it is possible to simultaneously detect arc locations on the electrode and influence their movements, using electromagnetic coils, in real time. In Phase II, the arc measurements will be coupled through feedback to control the arc distribution in an industrial-scale research VAR, providing proof of concept at industrial scale. In so doing, the optimal electromagnetic coil geometry, hardware, and materials for driving the arc motion at scale will be identified and constructed. A series of industrial experiments are planned to validate the control system. The chemical composition of the ingots produced during controlled and uncontrolled conditions will be characterized to correlate defects with observed arc behaviors and to identify optimal control parameters. Similarly, the measured arc distributions will be used to validate the computational solidification modeling, which will be used to identify probable defect regions. The combination of experimental data and validated simulation results will be used to inform the VAR feedback control system regarding optimal arc distribution, yielding an improved control strategy for tailoring the melt process and improving ingot quality.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.EMISSOL LLCEmissol LLCMansour Masoudi(425) 231-1686mansour.masoudi@emissol.com09/17/2018$746,477$746,47709/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Novel Urea Mixer to Enable Low Temperature Reduction of Diesel Exhaust Nitrogen Compounds1831231079518470SMALL BUSINESS PHASE IIAnna Brady-Estevez(703) 292-7077abrady@nsf.gov16300 Mill Creek Blvd. Ste 208-FMill CreekWA98012-1279Mill CreekUS01Emissol, LLC16300 Mill Creek Blvd,Suite 208FMill CreekWA98012-0002Mill CreekUS01The broader impact/ commercial potential of this Small Business Innovation Research (SBIR) project includes reducing emission of Diesel engines' toxic nitrogen oxides (NOx) in challengingly low temperature exhaust operations, while eliminating damaging urea deposits saving warranty costs for vehicle manufacturers, saving fuel, reducing greenhouse gases CO2 and N2O as well as particulate matter, while potentially enabling downsizing the complex and costly diesel emission control systems. The novel technology developed in this SBIR project may be configured for retrofitting existing diesel platforms. Nitrogen oxides pose risks to human respiratory and pulmonary systems, are associated with forming ground level ozone, photochemical oxidants, acid rain and fine particles, amongst a variety of their detriments, and their emission is therefore regulated. Our concept, when successful, will therefore make available a broad value proposition to the society, the environment and to the mobility industry. Finally, the insights developed into its gas phase reactions may have applications in other branches of science and technology.
This SBIR Phase II project proposes to resolve a currently unmet need in mitigating emission of toxic nitrogen oxides (NOx) from diesel engines, especially in low exhaust temperatures such as when the vehicle operates in stop-and-go, in local delivery or when idles its engine. The goal of this project is to develop a low cost, easy-to-fit and simple-to-integrate novel technology enabling low temperature Diesel NOx reduction. Continuing our successful Phase I research results, in this Phase II project more advanced prototypes will be developed and tested in low-temperature exhaust conditions, demonstrating rapid reduction of NOx on a commercially-available Selective Catalytic Reduction (SCR) catalyst, while evaluating the impact on lowering greenhouse gases CO2 and N2O. High fidelity computer simulations will be heavily utilized to further our understanding of underlying mechanisms such as the gas-phase reactions as well as to accelerate the development path. The project outcome is expected to alleviate a remaining challenge in Diesel emission control and to be rapidly welcome by the Diesel engine and vehicle industry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF BOSTON UNIVERSITYTrustees of Boston UniversityMagaly Koch(617) 353-7302mkoch@bu.eduSucharita Gopal09/17/2018$199,304$199,30410/01/201809/30/2021GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITIRES Track I: Collaborative Research: U.S.-Indonesian Research Experience for Students on Sustainable Adaptation of Coastal Areas to Environmental Change1827024049435266049435266IRES Track I: IRES Sites (IS)Maija M Kukla(703) 292-8710mkukla@nsf.gov881 COMMONWEALTH AVEBOSTONMA02215-1300BostonUS07Trustees of Boston University881 Commonwealth Ave.BostonMA02215-1300BostonUS07This is a collaborative three year IRES project for 18 US students to gain international research experience in earth, life and data sciences as applied to the coastal region of Northern Central Java, Indonesia. The collaborative activities will be performed in partnership between Boston University (BU), Tufts University (TU) and the University of Diponegoro (UNDIP), Semarang, Indonesia. A cohort of six students per year will gain hands-on laboratory and field experience in coastal zone research during a six-week stay at the foreign institution.
Coastal cities worldwide are facing the enormous task to become resilient against physical, social and economic challenges, in addition to challenges due to climate variations. Semarang (Indonesia) is one of the cities that exemplifies the multiple threats affecting society, economy, environment, and infrastructure. Assessing the impacts of present and future coastal hazards requires an understanding of the complex interactions between geological, hydrological, biophysical and socioeconomic systems. This can be best achieved by an integrated approach that includes research on both land and sea dynamics to identify natural and anthropogenic factors, their relative influences and related consequences. This project seeks to undertake effective, innovative, and transformative research to understand how coastal environments respond to natural and anthropogenic factors. Geospatial technology combined with big data analytics will be applied to assessing and monitoring the effects of coastal hazards with the goal to enable the sustainable adaptation of coastal areas to global environmental change. Students will learn data acquisition techniques and the ability to analyze and interpret scientific information.
The proposed research will combine field experience with cutting edge geospatial technology and data analytics to investigate the following research questions:
1. Is land subsidence in Semarang coastal area mainly caused by natural or anthropogenic processes? Or both? How can we determine the prevailing factors; whether it is due to groundwater abstraction, tectonic movement, volcanic activities or a combination of factors?
2. To what extent is the marine productivity of coastal waters near Semarang city affected by changing climatologic conditions of oceanic and atmospheric parameters in Java Sea? How is climate variations impacting fisheries resources and the economic productivity of coastal communities? How can we build models that show the linkages?
3. How can we effectively monitor and assess coastal marine ecosystems health and productivity? Are artificial patch reefs and mangrove reforestation efforts in Semarang coastal region effective solutions for protecting and rehabilitating coastal ecosystems?
4. How can geospatial technology and big data analytics help in revealing crucial interactions between ecological, economic and policy aspects to assess and manage the environmental risks? How can we measure and assess the changes in food intake pattern and food safety in relation to extreme weather and coastal hazards?
This project will establish a long term collaborative research and training program between US and Indonesian faculty and students. US students majoring in STEM fields will have an opportunity to conduct research and field work in an international and multi-disciplinary setting by engaging in problem solving research activities. They will be mentored by foreign collaborators and US PIs through web video conferencing and workshops jointly taught at the collaborating institution. The IRES experience is expected to a) broaden and leverage partnerships with overseas institutions, b) enhance US-student global awareness and perspectives, and c) develop multi-disciplinary themes that improve understanding of global change such as coral bleaching, habitat diversity, and coastal hazards. Research findings will be disseminated through peer-reviewed publications and presentations at conferences. In partnership with UNDIP and relevant agencies in Northern Central Java region, decision support products resulting from this project will be distributed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.OHIO STATE UNIVERSITY, THEOhio State UniversityEmre Ertin(614) 688-3928ertin.1@osu.edu09/17/2018$224,830$224,83010/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research1823070832127323001964634COMPUTING RES INFRASTRUCTURETonya Smith-Jackson(703) 292-5179tsmithja@nsf.govOffice of Sponsored ProgramsColumbusOH43210-1016ColumbusUS03Ohio State University2015 Neil AvenueColumbusOH43210-1241ColumbusUS03The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.
MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF CALIFORNIA, LOS ANGELESUniversity of California-Los AngelesMani B Srivastava(310) 267-2098mbs@ucla.eduVivek Shetty09/17/2018$299,993$299,99310/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research1822935092530369071549000COMPUTING RES INFRASTRUCTURETonya Smith-Jackson(703) 292-5179tsmithja@nsf.gov10889 Wilshire BoulevardLOS ANGELESCA90095-1406Los AngelesUS33University of California-Los AngelesECE Dept, 1762 Boelter HallLos AngelesCA90095-1594Los AngelesUS33The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.
MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNAVCO, INCUNAVCO, Inc.Meghan Miller(303) 381-7514Meghan@unavco.orgCharles M Meertens, Glen S Mattioli, Donna Charlevoix09/17/2018$1$110/01/201809/30/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth Ssystem Dynamics: Geodetic Facility for the Advancement of Geoscience (GAGE)1724794142357032GAGERussell C. Kelz(703) 292-4747rkelz@nsf.gov6350 Nautilus Dr.BoulderCO80301-5394BoulderUS02UNAVCO, Inc.6350 Nautilus DriveBoulderCO80301-5394BoulderUS02UNAVCO will develop, operate, and maintain a distributed, multi-user Geodetic Facility for the Advancement of GEoscience (GAGE). Geodesy characterizes the Earth's time varying shape, orientation in space, mass distribution, and gravity field. It has revolutionized the geosciences, by measuring Earth changes with unprecedented spatial and temporal resolution. The GAGE facility employs expert professional staff, with guidance provided by the scientific community, to manage and operate a set of foundational geodetic capabilities that are essential for current research support, as well as frontier geodetic activities that will enable future research. The facility will promote advances in our understanding of continental deformation; tectonic plate boundary processes; the processes that drive earthquakes, volcanic eruptions and landslide hazards; continental water storage, atmospheric, ice sheet and glacier dynamics; and interactions among these components of the Earth system. The geodetic capabilities provided through the GAGE facility contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data products from GAGE will be used by federal agencies including the National Aeronautics and Space Administration, the United States Geological Survey and the National Oceanic and Atmospheric Administration, for missions including spacecraft positioning, satellite orbit, and timing corrections; earthquake, tsunami, and volcano early warning; weather forecasting; water resources; and environmental management. State departments of transportation will use GAGE data to help support traffic monitoring and control and increasingly GAGE data will support commercial sector positioning needs including for agriculture, construction and surveying, transportation (including air, rail, and maritime), mining and resource exploration, and fleet vehicle tracking.
The GAGE facility will manage and operate: 1) global and regional continuously operating Global Navigational Satellite Systems (GNSS) and complementary geodetic technology networks; 2) portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) geodetic instrumentation testing and support service; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs that foster the development of the next generation geosciences workforce, are designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences, and engage the public by highlighting advances in geophysical sciences and their societal relevance. Innovative and transformative research that will benefit from GAGE examines both the dynamics of individual processes and the nonlinear interactions within and among larger Earth systems. The study of active processes from geocenter motion to the studies of the lithosphere, cryosphere, hydrosphere, and atmosphere requires understanding of the coupling and feedbacks across a range of length and time scales, and between the solid Earth and its fluid envelopes, in both physical and biological environments. Under NSF, and NASA partner agency support for GAGE, UNAVCO will integrate and federate a set of currently operated but at present independently managed GNSS stations to form the Network of the Americas (NOTA). UNAVCO will modernize NOTA stations with state-of-the-art, multi-sensor, multi-GNSS, receivers with real-time streaming data and analysis. These enhancements will enable higher precision positioning than currently possible and new application of GNSS data that can be used for geohazards warning systems, study of ocean and atmosphere dynamical behavior, and observation of key environmental parameters such as water storage, soil moisture, and sea and lake-level changes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CLEMSON UNIVERSITYClemson UniversityStephen Kaeppler(262) 707-0932skaeppl@clemson.edu09/17/2018$144,653$144,65312/17/201707/31/2019GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: CEDAR--A Long-term Investigation of Auroral and Tidal Forcing of E-region Thermospheric Winds at High Latitudes1853408042629816042629816AERONOMYCarrie E. Black(703) 292-8519cblack@nsf.gov230 Kappa StreetCLEMSONSC29634-5701US03Clemson UniversitySC29634-0001ClemsonUS03This project will use an 8-year data set from the Poker Flat Incoherent Scatter Radar (PFISR) to investigate the climatology and variability of high-latitude lower thermospheric winds. The analysis will address questions of the relative contribution of energy and momentum transfer from different sources. A long-term database of wind profiles will be developed and made available to the community to be used for testing of complex models.
This study will advance the understanding of ion-neutral coupling and energy, mass and momentum transfer between the magnetosphere, thermosphere, and atmosphere, and will investigate auroral effects on lower thermospheric winds. Case studies will be used to examine events of strong atmospheric or auroral forcing. The long-term data base will provide information about trends in lower thermospheric winds and which forcing mechanisms are most responsible for long-term variability.UNIVERSITY OF NEW MEXICOUniversity of New MexicoMarek Osinski(505) 272-7812osinski@chtm.unm.eduRoman Sobolewski, Arash Mafi, Ganesh Balakrishnan09/17/2018$749,998$749,99810/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: Integrated Silicon Photonics Platforms for Scalable Quantum Systems1842712868853094784121725COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov1700 Lomas Blvd. NE, Suite 2200AlbuquerqueNM87131-0001AlbuquerqueUS01University of New MexicoNM87131-0001AlbuquerqueUS01Quantum information processing (QIP) relies on the extraction, processing and manipulation, as well as transmission and detection of information by exploiting quantum properties of light and matter. QIP is expected to be used to secure and scale-up multiparty quantum computations to tackle computational problems that currently remain outside the reach of computers, such as large-scale molecular simulations for materials design and drug discovery; or it can connect a network of distributed quantum sensors for ultraprecise measurements with applications to biological imaging, gravitometry, and position navigation-timing. In a general landscape of QIP, quantum communications plays a special role, because it can be used to implement a secure data transmission network, leveraging the concept of quantum cryptography, where the security of transmission is guaranteed by the basic laws of quantum physics. Over the last decade, there has been tremendous progress in science and technology related to the generation, manipulation, storage, propagation, and detection of photons for QIP. Much of this progress has been focused on developing individual device components that satisfy the rather stringent requirements of QIP at the single-photon level. Integrating these individual components into a complete quantum-communication system with optimized operation requires an interdisciplinary approach. The move beyond individual discrete components necessitates a new paradigm that will integrate various components on a single chip. The main vision of this research is to push the frontiers of engineering in quantum technologies by implementing a silicon-based integrated platform and exploring the interactions of quantum devices in a quantum network. In addition to the advancement of the new science and technology, a major outcome will be the exposure of undergraduate and graduate students working on this project to a broad range of topics in an interdisciplinary environment. This broad teaching/research experience is a platform to train the highly skilled workforce of the future.
This transformative project will integrate novel devices for the generation, manipulation, propagation, and detection of single and entangled photons for quantum information processing in a silicon photonics platform that can be used to implement a large-scale quantum communication network. This is a highly interdisciplinary project that brings together expertise in materials science and engineering; semiconductor fabrication, processing, and devices; superconducting device physics; classical nonlinear and quantum optics; and optical communications to solve technical challenges for the development and realization of a scalable integrated quantum communication platform. The research covers both design and fabrication of single-photon and entangled photon pair sources, single-photon detectors, and integrated channels to manipulate photons, as well as experiments to characterize the quantum nature of the photonic states for implementation in viable quantum communication protocols. The proposed integrated platform is very promising for implementation in a quantum communication system network, as well as in development and realization of large-scale systems. The individual components and devices that will be used in the proposed research are quite novel and amenable to scalable integration using standard semiconductor device processing technologies. Superconducting quantum-dot light-emitting diodes, whose operation is based on Cooper-pair interband transition in a semiconductor, will be developed to generate single- and pair-photon states. For single-photon detection, traveling-wave superconducting nanostripe single-photon detectors will be developed and integrated in the device platform. The on-demand electrically driven photon sources, as well as single-photon detectors, will be used along with passive silicon nitride waveguides, all integrated on the silicon substrate, to study various scenarios for quantum information processing implementations, such as characterization of path-entangled photons, multi-qubit entanglement, quantum state tomography, and, potentially, as a proof-of-concept for quantum communication protocols.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.STEVENS INSTITUTE OF TECHNOLOGY (INC)Stevens Institute of TechnologyYuping Huang(201) 216-5709Yuping.Huang@stevens.eduMichael Vasilyev09/17/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: A Chip-integrated Platform for Photon-Efficient Quantum Communications1842680064271570064271570COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govCASTLE POINT ON HUDSONHOBOKENNJ07030-5991HobokenUS08Stevens Institute of TechnologyCASTLE POINT ON HUDSONHobokenNJ07030-5991HobokenUS08Nontechnical Abstract:
Quantum communication exploits the fundamental laws of physics to reliably secure private information networking even over untrusted channels. Despite rapid progresses in research and technology demonstrations, its large-scale deployment in practical settings still faces significant difficulties such as limited distance, low data rates, high susceptibility to channel disturbances, and disproportional operating overhead. This project aims to address those challenges by developing chip-integrated devices and sub-systems for preparation and detection of photonic signals in advantageous quantum states. They will be assembled to create innovative systems for line-of-sight applications robust against inferior weather conditions, ultra-efficient information encoding and decoding on single photons, and optimized hybrid quantum communication over both free space and optical fibers. This project will be carried out collaboratively by research groups from Stevens Institute of Technology and University of Texas at Arlington. Students from both institutes will be supported, motivated, and trained to work at the intersection of device integration, quantum optics, high-speed electro-optic circuits, and communication systems. A workforce with such balanced trainings and knowledge bases will contribute significantly to the industrial development of quantum technologies. At Stevens, a weekend-lab visit will be hosted each semester open to public to showcase the merging frontiers of quantum physics and nanophotonics. At Arlington, guided lab visits will be organized during the Engineering Week and K-12 summer camps. Both groups will continue to attract members from under-represented groups and help them launch scientific and engineering careers.
Technical Abstract:
This project will develop a highly-integrated quantum photonic platform based on lithium niobate thin films for modular quantum transceivers, whose unique capabilities include entanglement generation over 3.2-micron spectral spacing, lossless photon waveform shaping on a picosecond timescale, disruptive receiver technology based on mode-resolving photon detection, and ultrafast optical time-division de-multiplexing for fast quantum signals. With these offerings, this new device platform will host innovative techniques for fast, robust, and photon-efficient quantum communications over both telecom fibers and free space. Three quantum communication systems will be targeted in this project. The first is an innovative mid-IR channel for weatherproof quantum communication over free space, which not only multiplies the communication speed and reach but may also provide a reliable, high-speed ground-space link for quantum satellite applications through further development. The second is ultra-photon-efficient quantum key distribution using overlapping time-frequency modes to significantly increase the key rate while also strengthening the channel security. Meanwhile, quantum bit locking will also be explored by unitary scrambling and de-scrambling single photons, as an alternative approach to high-speed quantum encryption. The third is an optimized hybrid quantum key distribution system over free space and optical fibers that could form the basis for the future versatile, resilient quantum networks.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.WASHINGTON STATE UNIVERSITYWashington State UniversityAnurag K Srivastava(509) 335-2348asrivast@eecs.wsu.eduAnjan Bose, Saeed Lotfifard, Adam Hahn, Paul Whitney09/17/2018$1,378,337$1,378,33710/01/201809/30/2023GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITFW-HTF: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency1840192041485301041485301FW-HTF: Advancing Cognitive anDavid Corman(703) 292-8950dcorman@nsf.gov280 LightyPULLMANWA99164-1060PullmanUS05WSU Energy Systems Innovation Center355 Spokane Street/EME 31PullmanWA99164-2752PullmanUS05The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by the National Science Foundation. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. Effective decision making by power grid operators in extreme events (e.g., Hurricane Maria in Puerto Rico, the Ukraine cyber attack) depends on two factors: operator knowledge acquired through training and experience, and appropriate decision support tools. Decision making in electric grid operation during extreme adverse events directly impacts the life of citizens. This project will augment the cognitive performance of human operators with new, human-focused decision support tools and better, data-driven training for managing the grid especially under highly disruptive conditions. The development of new generation of tools for online knowledge fusion, event detection, cyber-physical-human analysis in operational environment can be applied during extreme events and provide energy to critical facilities like hospitals, city halls and essential infrastructure to keep citizens safe and avoid economic loss for the Nation. Higher performance of operators will improve worker quality of life and will enhance the economic and social well-being of the country. The project's training objectives will leverage existing educational efforts and outreach activities and we will publicize the multidisciplinary outcomes through multiple venues.
The proposed project will integrate principles from cognitive neuroscience, artificial intelligence, machine learning, data science, cybersecurity, and power engineering to augment power grid operators for better performance. Two key parameters influencing human performance from the dynamic attentional control (DAC) framework are working memory (WM) capacity, the ability to maintain information in the focus of attention, and cognitive flexibility (CF), the ability to use feedback to redirect decision making given fast changing system scenarios. The project will achieve its goals through analyzing WM and CF and performance of power grid operators during extreme events; augmenting cognitive performance through advanced machine learning based decision support tools and adaptive human-machine system; and developing theory-driven training simulators for advancing cognitive performance of human operators for enhanced grid resilience. A new set of algorithms have been proposed for data-driven event detection, anomaly flag processing, root cause analysis and decision support using Tree Augmented naive Bayesian Net (TAN) structure, Minimum Weighted Spanning Tree (MWST) using the Mutual Information (MI) metric, and unsupervised learning improved for online learning and decision making. Additionally, visualization tools have been proposed using cognitive factor analysis and human error analysis. We propose a training process driven by cognitive and physiometric analysis and inspired by our experience in operators training in multiple domain: the power grid, aircraft and spacecraft flight simulators. A systematic approach for human operator decision making is proposed using quantifiable human and engineering analysis indices for power grid resiliency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VANDERBILT UNIVERSITY, THEVanderbilt UniversityGautam Biswas(615) 343-6204gautam.biswas@vanderbilt.eduAbhishek Dubey09/17/2018$323,081$323,08110/01/201809/30/2023GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITFW-HTF: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency1840052965717143004413456FW-HTF: Advancing Cognitive anDavid Corman(703) 292-8950dcorman@nsf.govSponsored Programs AdministratioNashvilleTN37235-0002NashvilleUS05Vanderbilt University1025 16th Avenue South Suite 102NashvilleTN37212-2328NashvilleUS05The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by the National Science Foundation. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. Effective decision making by power grid operators in extreme events (e.g., Hurricane Maria in Puerto Rico, the Ukraine cyber attack) depends on two factors: operator knowledge acquired through training and experience, and appropriate decision support tools. Decision making in electric grid operation during extreme adverse events directly impacts the life of citizens. This project will augment the cognitive performance of human operators with new, human-focused decision support tools and better, data-driven training for managing the grid especially under highly disruptive conditions. The development of new generation of tools for online knowledge fusion, event detection, cyber-physical-human analysis in operational environment can be applied during extreme events and provide energy to critical facilities like hospitals, city halls and essential infrastructure to keep citizens safe and avoid economic loss for the Nation. Higher performance of operators will improve worker quality of life and will enhance the economic and social well-being of the country. The project's training objectives will leverage existing educational efforts and outreach activities and we will publicize the multidisciplinary outcomes through multiple venues.
The proposed project will integrate principles from cognitive neuroscience, artificial intelligence, machine learning, data science, cybersecurity, and power engineering to augment power grid operators for better performance. Two key parameters influencing human performance from the dynamic attentional control (DAC) framework are working memory (WM) capacity, the ability to maintain information in the focus of attention, and cognitive flexibility (CF), the ability to use feedback to redirect decision making given fast changing system scenarios. The project will achieve its goals through analyzing WM and CF and performance of power grid operators during extreme events; augmenting cognitive performance through advanced machine learning based decision support tools and adaptive human-machine system; and developing theory-driven training simulators for advancing cognitive performance of human operators for enhanced grid resilience. A new set of algorithms have been proposed for data-driven event detection, anomaly flag processing, root cause analysis and decision support using Tree Augmented naive Bayesian Net (TAN) structure, Minimum Weighted Spanning Tree (MWST) using the Mutual Information (MI) metric, and unsupervised learning improved for online learning and decision making. Additionally, visualization tools have been proposed using cognitive factor analysis and human error analysis. We propose a training process driven by cognitive and physiometric analysis and inspired by our experience in operators training in multiple domain: the power grid, aircraft and spacecraft flight simulators. A systematic approach for human operator decision making is proposed using quantifiable human and engineering analysis indices for power grid resiliency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MISSISSIPPI VALLEY STATE UNIVERSITYMississippi Valley State UniversityMarcus Golden(662) 254-3425marcus.golden@mvsu.edu09/17/2018$26,700$26,70010/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Identifying Participation Barriers to Computer Science Education in Rural Mississippi1837543073538654073538654STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.gov14000 Highway 82 WItta BenaMS38941-1400Itta BenaUS02Mississippi Valley State University14000 Highway 82 West, MVSU 7257Itta BenaMS38941-1400Itta BenaUS02The primary goal of the small strand, K-14 project "Collaborative Research: Identifying Participation Barriers to Computer Science Education in Rural Mississippi" is to develop a researcher-practitioner partnership (RPP) to identify barriers to participation in computer science education in high poverty, rural areas of Mississippi. In the past two years, a collaborative effort between the Mississippi Department of Education (MDE) and Mississippi State University's (MSU's) Research and Curriculum Unit (RCU) implemented a statewide computer science pilot offered free of charge to K-12 schools. Entering the third year of the pilot, 74 of 148 school districts in the state are now offering computer science courses; however, it has been observed that districts situated in the most rural, highest poverty, and lowest income areas in the state (primarily the Delta region) are not participating in the opportunity to provide their teachers free computer science professional development and thereby offer students access to courses that would begin preparing them for jobs in a very high-demand, high-salary career. Through a RPP, issues and perceptions will be investigated to determine why these districts are not taking advantage of this opportunity to offer computer science education in the classrooms.
This collaborative project between MSU and Mississippi Valley State University (MVSU), a four-year institution of higher learning located in the Delta, will form a partnership with teachers, administrators, and counselors from six districts in the area surrounding MVSU, as well as the local community college, business owners, community leaders, and parents, to identify issues acting as barriers or constraints to computer science education opportunities. Identifying and addressing the root causes of the lack of participation in these types of demographic and geographic areas will give a voice to those who are most directly involved, while also transforming perceptions of computer science and broadening participation in the field based on contributions from more diverse groups, primarily African American teachers and students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CLEMSON UNIVERSITYClemson UniversityJacob Sorber(801) 885-5071jsorber@clemson.eduKelly Caine09/17/2018$398,359$196,39010/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITABR: Collaborative research: Smart earpiece for supporting healthy eating behaviors1835974042629816042629816Computer Systems Research (CSRM. Mimi McClure(703) 292-5197mmcclure@nsf.gov230 Kappa StreetCLEMSONSC29634-5701US03Clemson University230 Kappa StreetClemsonSC29634-0001ClemsonUS03Obesity is one of the most pressing health challenges faced by our country, and has been the target of much attention in the mobile health (mHealth) community. While the science of obesity indicates that diet is a major factor in healthy weight management, scientists are still not able to effectively, quickly and easily measure eating behavior. This project's goal is to develop a digital earpiece comfortable enough to wear (on or near the ear) that can sense and detect eating behavior. The project's long-term vision is to enable health researchers to better understand eating-related behaviors and, subsequently, to support the development of effective interventions that promote healthy diet and behavior.
Ultimately, a better understanding of eating-related behaviors, and better design of effective interventions regarding eating behavior, will have profound impact on personal and public health as well as the national economy. The project's hardware and software prototypes will be shared widely in the research community to enable experimentation around the sensing and interaction opportunities possible in an earpiece device. Furthermore, the project directly involves undergraduate and graduate students in interdisciplinary research, and outreach to middle-school students, expanding the supply of scientists educated in this important emerging topic.
The project will build a prototype wireless earpiece, with low-power (microwatt-scale) electronics and software sufficient to allow for the battery to last a full waking day; to develop efficient algorithms for detecting and distinguishing health-related behaviors; and to develop easy and effective means for the wearer to interact with the earpiece and its applications.
The team expects to answer scientific questions important to achieving the above goals. Specifically, they seek to advance scientific knowledge through the design and development of a wireless earpiece capable of sensing behavior and interacting with its wearer; develop novel low-power analog electronics and distributed software algorithms for inferring relevant behaviors from sensor data; develop novel interaction modalities involving bone-conduction audio between the earpiece and its wearer, complemented by tactile interfaces on the earpiece, on the skin, or on auxiliary devices like a wristband or smartphone; and validate these approaches through user studies and experiments inside and outside the lab.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CAL POLY CORPORATIONCalifornia Polytechnic State University FoundationJane Lehr(805) 756-2982jlehr@calpoly.edu09/17/2018$2,552,890$2,552,89010/01/201809/30/2023GrantNSF4900490047.076045176 H-1B FUND, EHR, NSFCollaborative Research - Enabling Transfer Student Access to Engineering1834128029326246029326246S-STEM:SCHLR SCI TECH ENG&MATHAlexandra Medina-Borja(703) 292-7557amedinab@nsf.govOne Grand AveSan Luis ObispoCA93407-0830San Luis ObispoUS24California Polytechnic State UniversityOne Grand AvenueSan Luis ObispoCA93407-0035San Luis ObispoUS24The NSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) program supports the retention and graduation of high-achieving, low-income students with demonstrated financial need. This project, at Allan Hancock College, Cuesta College, and California Polytechnic State University (Cal Poly) will fund fifty 2-year scholarships at Allan Hancock and fifty 2-year scholarships at Cuesta College. The Scholars will be in cohorts of 25 students who are pursuing transfer to a BS-granting institution to study engineering. This project will also fund sixty-two scholarships at Cal Poly for transfer students from Allan Hancock and Cuesta, thus supporting the Scholars until their graduation with a BS degree in engineering. Allan Hancock and Cuesta are highly-ranked Hispanic-Serving Institutions. Cal Poly is one of only five comprehensive polytechnic universities in the nation, and is ranked as a one of the nation's top public masters-level institutions. This project will build on and strengthen collaborations to increase the number of low-income students who begin their engineering education at Allan Hancock or Cuesta, transfer to Cal Poly, are retained in and graduate with a BS degree, and enter a STEM graduate program or the STEM workforce.
Specific program activities seek to remove or minimize economic barriers and support student development in five areas: 1) academic; 2) engineering transfer/career path; 3) personal, via Strengths and Growth Mindset training from a Social Justice perspective; 4) connection; and 5) professional. The project will also adopt essential evidence-based transfer practices, continuously assessing progress achieved in this area within and across each participating campus to institutionalize more robust transfer pathways and support the success of all future STEM transfer students at Allan Hancock, Cuesta, and Cal Poly. The project will include two research strands designed to advance understanding of strategies that enhance transfer student success in a career in engineering. The first research project will use social network analysis, survey methods, and qualitative interviews to advance understanding of how project activities contribute to a) growth of student social networks; b) increase in student resilience, confidence, sense of community, and sense of belonging; and c) whether growth in these areas is related to increased student retention, pre-transfer success, transfer, and post-transfer success. The second research project will integrate pre- and post-transfer Scholars into existing research to advance understanding of student motivations and perceptions when choosing to participate in (or leave) co-curricular team projects in engineering. The integration of Scholars allows for investigation of whether decision-making factors regarding participation in co-curricular team projects are consistent for student groups at community colleges and four-year institutions, and for students who are directly admitted or transfer to a 4-yearinstitution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.P C KRAUSE AND ASSOCIATES INCPC Krause and Associates, Inc.Alex Heltzel(765) 464-8997heltzel@pcka.com09/17/2018$747,765$747,76509/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Passive Radiative Composite Material1831805161183322161183322SMALL BUSINESS PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov3000 Kent Avenue, Suite C1-100West LafayetteIN47906-1108West LafayetteUS04PC Krause and Associates, Inc.3000 Kent Avenue, Suite C1-100West LafayetteIN47905-1075LafayetteUS04The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be observed through a direct reduction in the energy consumption required by large industrial facilities, commercial buildings, campuses, and homes. Due to reduced cooling demands as a result of carefully designed radiative properties, the sustainability of federal and industry facilities will be significantly improved with the installation of passive radiative composite (PRC) roofing material for building energy management. The market demand for cool roofing materials has exceeded $1 Billion, annually, and is expected to grow with increasing need and return on investment. PRC roofing material can expect to compete in a growing industry due to non-trivial improvement over state-of-the-art options in commercial cool roofing products and the economic fabrication method identified in the PRC conceptual design stage. Opportunities extend beyond structural thermal management to a variety of cooling needs including refrigerated transportation and storage. The development of PRC roofing will advance understanding and use of spectrally-selective materials designed for intelligent control of thermal radiation.
The proposed project will provide critical design, testing, and experimental validation needed to transition PRC technology into the commercial sector. Designs based on electromagnetic and thermal modeling include composite material options capable of providing passive radiative flux of over 100 Watts per square meter of installed material. This passive cooling advantage, relative to current commercial cool roofing materials, is expected to create significant long-term cost savings and reduction in fossil fuel usage for climate controlled structures. PRC material properties designed to be spectrally selective offer the opportunity for intelligent thermal management through reflection of solar and near-infrared portions of the radiative spectrum, while emitting strongly in the 8-13 micron atmospheric transmission window. A primary objective of the SBIR project is to optimize PRC designs considering full spectrum properties with three criteria in mind: thermal efficiency improvement, durability, and large batch manufacturing economy. Demonstration of PRC-based roofing materials on full-scale test structures will quantify passive cooling power and robustness to weathering, positioning PRC-based roofing for introduction by a commercial manufacturing partner.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.VIA SEPARATIONS, LLCVia Separations, LLCShreya Dave(781) 354-7945sdave@mit.edu09/17/2018$728,413$728,41309/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Robust Nanofiltration to Enable Challenging Chemical and Pharmaceutical Separations1831203080470259SMALL BUSINESS PHASE IIRajesh Mehta(703) 292-2174rmehta@nsf.gov381A Huron AvenueCambridgeMA02138-6832CambridgeUS05Via Separations, LLC501 Massachusetts AvenueCambridgeMA02139-4018CambridgeUS07This SBIR Phase II project focuses on advancing the domestic manufacturing capabilities for high-value nanomaterials for new membrane materials. Previously, the company has developed a novel membrane material with considerable economic, environmental, and nutritional impact in industrial process applications. Commercially available nanofiltration (NF) membrane systems employ polymer membranes, which have inherent chemical and thermal intolerance and are therefore difficult to clean or cannot be used in all separation streams. Meanwhile, 12% of US energy consumption is dedicated to thermal separations, a number that can be cut by a factor of 10 with appropriate physical separation technologies. This technology has applications across food & beverage processing, pharmaceutical production, semiconductor manufacturing, and chemical/petrochemical refining.
Creating nanometer-scale features on large areas (tens of square meters) will enable technical opportunities for a multitude of products and applications. In this SBIR Phase II project, the company is conducting process development, pilot demonstration, and scale up efforts toward coating graphene oxide thin films for nanofiltration membrane separations applications. Today?s membrane processes are limited by the selectivity and durability of the nanofiltration membrane. Improved selectivity and operational conditions from the material platform enables improved downstream processes, and new product development. The technology is tolerant to elevated temperatures, extreme pH, organic and chlorinated solvents, and high levels of oxidizers. Transitioning from thermal separations to membrane separations saves 90% of the required energy. Meanwhile, payback time is < 3 months when improving clean-in-place (CIP) protocol for existing NF processes. This is a game changer for the separations industry. Key separations of interest include desalting, whey concentration, sugar fractionation, fatty acid separation, nutraceutical extraction, pharmaceutical purification and black liquor concentration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.SARATOGA ENERGY RESEARCH PARTNERS, LLCSaratoga Energy Research Partners LLCBenjamin M Rush(510) 390-5121ben@saratoga-energy.com09/17/2018$722,669$722,66909/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Electrolytic Generation of Low-Cost, High-Density Carbon Nanotubes for High-Performance Lithium-Ion Batteries1831078078668529SMALL BUSINESS PHASE IIAnna Brady-Estevez(703) 292-7077abrady@nsf.gov820 Heinz AveBerkeleyCA94710-2737BerkeleyUS13Saratoga Energy Research Partners LLC820 Heinz AvenueBerkeleyCA94710-2737BerkeleyUS13The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is multilayered. First, there is the potential for creation of a carbon nanotubes manufacturing industry in the United States that will create hundreds of high-paying domestic manufacturing jobs advance U.S. leadership and knowledge in industrial electrochemistry. Secondly, Saratoga Energy's technology has the potential to benefit the United States economy by increasing the cost-competitiveness and performance of lithium-ion batteries, paving the way to the broader adoption of electric vehicles and grid/renewable energy storage. In turn, this will help reduce the strategic importance of oil, the cost of securing global oil supplies, as well as greenhouse gas emission. While lithium-ion batteries are the focus of this body of work, carbon nanotubes (CNTs) are also used in a variety of other applications - advanced composite materials, nanotechnology, catalyst supports, water filtration, and other areas of commercial impact.
This SBIR Phase II project proposes to 1) electrochemically characterize carbon nanotubes as a cathode conductive additive for high-performance lithium-ion battery applications and 2) construct a small pilot-scale carbon nanotube manufacturing unit capable of producing 1 kg of product per day for retail distribution. Saratoga Energy Research Partners, LLC (Saratoga Energy), has developed a high-selectivity electrochemical process to convert carbon dioxide into carbon nanotubes. In the work conducted thus far, Saratoga Energy has established that its carbon nanotubes can be manufactured at a cost ~50X cheaper than the market price for state-of-the-art battery-grade carbon nanotubes. Battery manufacturers use carbon nanotubes to enable the reduction of conductive additive content in the cathode, thus improving specific and volumetric energy density. Carbon nanotubes also act as a reinforcing agent in the electrodes improving their mechanical properties. This is important for the battery assembly process but also for battery life performance, as the carbon nanotube network maintains a high level of cohesion of the electrodes upon repeated charge-discharge cycles. However, today, the high price of commercial carbon nanotubes limits their use, which will be addressed by our lower cost CNTs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.PENNSYLVANIA STATE UNIVERSITY, THEPennsylvania State Univ University ParkAlan Wagner(814) 856-3138alan.r.wagner@psu.eduMinghui Zhu09/17/2018$990,462$990,46210/01/201809/30/2022GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITNRI: INT: COLLAB: Interactive and collaborative robot-assisted emergency evacuations1830390003403953003403953National Robotics InitiativeRalph Wachter(703) 292-2653rwachter@nsf.gov110 Technology Center BuildingUNIVERSITY PARKPA16802-7000University ParkUS05Pennsylvania State Univ University ParkPA16802-7000University ParkUS05Many emergencies require people to evacuate a building quickly. During an emergency, evacuees must make quick decisions, so they tend to rely on default decision making that may put them at risk, such as exiting the way they entered, following a crowd, or sheltering in place. When a crowd attempts to exit through a single exit, choke points and crowd congestion may impede the safe flow of evacuees, potentially resulting in a stampede of people and the loss of human lives. Mobile robots are increasingly being deployed as assistants on city streets and in hotels, shopping centers and hospitals. The future ubiquity of these systems offers an opportunity to change how people are evacuated from dangerous situations. In particular, when compared with traditional emergency infrastructure, such as fire alarms and smoke detectors, mobile robots can achieve better situation awareness and use this information to expedite evacuation and enhance safety. Additionally, mobile robots can be used in risky and life-threatening situations, such as chemical spills or active shooter scenarios, which present dangers to human first responders.
This project aims to derive a scalable design framework and develop an embodied multi-robot evacuation system where multiple mobile robots, originally tasked for different purposes, serve as emergency evacuation first responders leading people to safety. In particular, multiple mobile robots efficiently coordinate with each other and actively interact with evacuees to maximize their egress. The project significantly contributes to the understanding of how people respond to a robots' directions and authoritative commands. Furthermore, the project implements these findings and demonstrates their effectiveness using real-world experiments with human subjects. Beyond emergency evacuation, the research findings can be extended to many other related areas, especially those involving cooperative robot teams that are embodied in an uncertain and dynamic physical world with the need to actively interact with humans; e.g., battlefield, law enforcement, urban transportation systems, manufacturing systems, rehabilitation and health management.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF ALASKA ANCHORAGEUniversity of Alaska Anchorage CampusPatrick F Sullivan(907) 440-2865pfsullivan@alaska.eduLee Ann Munk09/17/2018$135,839$135,83910/01/201809/30/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of a State-of-the-Art Water Isotope Analyzer to Monitor Changes in the Coupled Climate System and Water Cycle at High Latitudes1828786076664986048679567MAJOR RESEARCH INSTRUMENTATIONPeter J. Milne(703) 292-4714pmilne@nsf.gov3211 PROVIDENCE DRIVEANCHORAGEAK99508-4614AnchorageUS00University of Alaska Anchorage Campus3211 Providence DriveAnchorageAK99508-4614AnchorageUS00The University of Alaska Anchorage's Environment and Natural Resources Institute (ENRI) stable isotope laboratory has a long history of serving a broad research community and fostering collaborations among academic and government scientists studying the Arctic. With this MRI award, the investigators will replace retired equipment with the purchase a new instrument to analyze the stable isotopes of hydrogen and oxygen with high precision on a fee-for-service basis. As components of water molecules, isotopes of hydrogen and water serve as valuable tracers within the coupled climate system and water cycle, and isotope data can be used to understand changes in air, water, and ice over time and space. In addition to supporting a wide range of scientific studies, the laboratory hosts tours for high school and undergraduate students and trains undergraduate and graduate students in analytical techniques as part of their coursework.
The investigators will purchase a new Picarro L2130-I cavity ring-down spectroscopy water isotope analyzer to replace retired, early models that have processed more than 50,000 water samples. Analytical capability will be expanded by adding a new vaporizer and autosampler and add to the suite of instruments operated and maintained in the Environment and Natural Resources Institute Stable Isotope Laboratory. This lab, the only of its kind in Southcentral Alaska, produces data that are used by academic and government scientists in Alaska and beyond to understand the hydrologic cycle and climate in the Arctic.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BAYLOR UNIVERSITYBaylor UniversityHo Wai Howard Lee(254) 710-3817Howard_Lee@baylor.eduMarlan O Scully, Zhenrong Zhang, Seunghyun Kim, Sunghwan Lee09/17/2018$689,500$689,50010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of 30kV Electron Beam Lithography System for Multidisciplinary Research on Nano-Photonics, Nano-Biophysics, Nano-Chemistry, and Nano-Electronics1828416007516735007516735MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.govOne Bear Place #97360WacoTX76798-7360WacoUS17Baylor UniversityOne Bear Place #97316WacoTX76798-7316WacoUS17The ability to pattern designed nanoscale structures precisely is critical for research in nanoscience. Electron Beam Lithography, which uses a scanning electron beam, is one of the most reliable and powerful methods to create patterns with sub-10 nm resolution in a relatively large surface area. This project enables Baylor University to acquire an Ultrahigh Resolution Electron Beam Lithography System for the development of a high-impact, multidisciplinary program of nanoscience research and education at Baylor University. Instrument users will include faculty and students from Baylor University's Physics, Electrical and Computer Engineering, Mechanical Engineering, Chemistry and Biochemistry, and Environmental Science departments. The instrument will expand nanofabrication capabilities at Baylor University for studying physics, optics, chemistry, biology sensing, and optical device applications on the nanometer scale. The instrument's capabilities will open the path for researchers to explore promising nanoscale sciences and applications. The electron beam lithography system will also be incorporated into education and outreach activities, including the Baylor Mayborn Museum events, online outreach activities, Baylor Summer Science Research Program, Advanced Instrumentation Workshop, and Optical Society of America events and workshops. The research and training opportunities provided by this nanofabrication instrument will align with Baylor University's strategic plan to advance research and education and strengthen the engagement with the community.
This project will acquire an Ultrahigh Resolution Electron Beam Lithography System to support nanoscience and nanotechnology research and education. The tool provides ultrahigh resolution patterning (<8 nm) in combination with the highest level of automation for complex applications. The thermal field emission filament technology, cross-over-free beam path, and column technology produce an extremely high beam current density, extremely low aberrations, fast writing speed, large field sizes, and millimeter-long periodic patterns with zero stitching errors. No other laboratory in the Central Texas region has this type of instrument critical to state-of-the-art nanoscience research. The instrument is ideally suited for research in nano-optics/photonics, nano-biophysics, nano-chemistry, and large-area nanoscale electronic and photonic devices. Examples of the nanoscale applications that can be fabricated include tunable ultrathin optical metasurface components, nanoscale and portable surface-enhanced coherent Raman sensors, point-of-care on-chip optical biosensors, plasmon-assisted photocatalytic reactors, efficient nanoscale bio-medical applications, and next-generation nano-electronic/photonic devices. The acquisition of this electron beam lithography system will not only enable innovative system-oriented nanoscience and nanodevice research activities at Baylor University and nearby colleges, but also facilitate the training of a new generation of students and postdoctoral researchers on nanoscience and nanoengineering at Baylor University.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CSU CHICO RESEARCH FOUNDATIONCalifornia State University, Chico Research FdtnZahrasadat Alavizalavi@csuchico.eduJinsong Zhang, Ozgul Yasar, Kathleen Meehan09/17/2018$175,305$175,30510/15/201809/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of FTIR Spectroscopic Imaging System towards material characterization with contributions to health, clean energy generation, and efficient processing techniques1827134612177162MAJOR RESEARCH INSTRUMENTATIONJenshan Lin(703) 292-7950jenlin@nsf.govOffice of Sponsored ProgramsChicoCA95929-0001ChicoUS01California State University, Chico400 West First StreetChicoCA95929-0001ChicoUS01The project will acquire a Fourier Transform Infrared (FTIR) spectroscopic imaging system. The FTIR spectroscopic imaging system will enable faculty and students at California State University, Chico (CSUC) to contribute to the knowledge base required to improve the health of humans, animals, and plants, contribute to the development of clean green energy generation, increase the lifespan and efficiency of materials in harsh environments, and develop more efficient processing techniques to fabricate various chemicals and materials. The acquired spectroscopic imaging system will support the development of interdisciplinary collaborations between faculty in the College of Agriculture, College of Natural Sciences, and College of Engineering, Computer Science, and Construction Management. Approximately 650 students from Chemistry, Biochemistry, Biology, Computer Engineering, Electrical Engineering, and Mechanical Engineering will use the FTIR spectroscopic imaging system or analyze data collected by this system. CSUC has significant student populations from underrepresented and underserved groups, including those who are first-in-family to enter college, veterans, and Hispanics. CSUC students will gain exposure to this state-of-the-art system and enhance their skills for both theoretical and experimental work.
The proposed FTIR spectroscopic imaging system will enable many research projects. The FTIR system with its ability to perform fast FTIR hyperspectral imaging makes it a powerful tool for the identification of key compounds in highly variable heterogeneous biomaterials as well as identification of unknown materials in a homogeneous matrix. An added benefit of FTIR spectroscopic imaging systems is that it is a non-invasive characterization tool, which makes it an emerging technology used in the structural analysis of biological samples. The research projects that will benefit from this system include: (a) the characterization of the plants containing terpene, a chemical that provide protections from herbivores and may have reduce healing inflammation and bacterial infections; (b) the study of bifunctional organic linker molecules as they bind to nanomaterials for photovoltaic and biochemical sensing applications; (c) the elucidation of reaction mechanisms including those involved in the synthesis of natural products such as antioxidants and the catalysis/generation of reactive oxygen species by wide bandgap nanoparticles; (d) the analysis of the surface configuration of metal and metal oxide nanoparticles (e.g., tin, which is an anode material for Li-ion batteries); and (e) the study of oxidation and reduction of particles in air and other environments coupled with the evaluation of techniques to improve the particles' stability or their reactivity. This system will be used to support several active research projects, to develop an undergraduate and graduate teaching laboratory, and to initiate new areas of research within the CSUC Electrical and Computer Engineering Department in collaboration with several other departments, schools, and colleges across the university.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF SOUTHERN CALIFORNIAUniversity of Southern CaliforniaMichael Neely(213) 740-3505mikejneely@gmail.com09/17/2018$174,765$174,76510/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSpecEES: Collaborative Research: Leveraging Randomization and Human Behavior for Efficient Large-Scale Distributed Spectrum Access1824418072933393072933393SpecEES Spectrum Efficiency, EMonisha Ghosh(703) 292-8746mghosh@nsf.govUniversity ParkLos AngelesCA90089-0001Los AngelesUS37University of Southern California3740 McClintock Ave EEB 520Los AngelesCA90089-0001Los AngelesUS37An explosion of low-cost wireless devices promises new applications and services in diverse domains, including health, transportation, energy, manufacturing, and entertainment. This project focuses on developing energy and spectrum-efficient, distributed multi-access strategies for dynamic and large-scale wireless networks under the stringent energy and delay requirements that are expected in emerging applications. This work will enable the development of a multitude of technologies that can improve the life of society-at-large. For example, this work can support the next generation of communication technologies for large-scale Internet of Things (IoT) applications and autonomous vehicle applications. Moreover, education is a core component of this project. New theories and algorithms developed in this project are integrated into the graduate-level courses at the three universities. Undergraduate and graduate students are involved in the project through the undergrad capstone and masters graduation projects at the Ohio State University.
This project explores the fundamental energy and spectrum-efficiency tradeoff of distributed spectrum access methods, and develops adaptive and correlated strategies that embrace and control randomness with efficiency guarantees for dynamic users with delay-sensitive traffic. In addition, the design incorporates humans into the loop by observing how humans react in simple multi-access games, providing simple human behavior models and simple human-perceived quality metrics, and by designing methods that can adapt to unexpected events or actions. A combined analysis and implementation approach of this project exploits high-dimensionality in the system while also overcoming difficulties for large-scale implementation and testing. In particular, the project develops mean-field techniques and analyses for large-scale spectrum access. Novel real-world experimentation strategies developed in this project emulate large-scale system operation in a small testbed by utilizing the simplification due to our randomized solutions and the integration of the aforementioned mean-field methods.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ARIZONA STATE UNIVERSITYArizona State UniversityLei Ying(480) 965-7003lying6@asu.edu09/17/2018$175,000$175,00010/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSpecEES: Collaborative Research: Leveraging Randomization and Human Behavior for Efficient Large-Scale Distributed Spectrum Access1824393943360412806345658SpecEES Spectrum Efficiency, EMonisha Ghosh(703) 292-8746mghosh@nsf.govORSPATEMPEAZ85281-6011TempeUS09Arizona State UniversityP.O. Box 876011TempeAZ85287-6011TempeUS09An explosion of low-cost wireless devices promises new applications and services in diverse domains, including health, transportation, energy, manufacturing, and entertainment. This project focuses on developing energy and spectrum-efficient, distributed multi-access strategies for dynamic and large-scale wireless networks under the stringent energy and delay requirements that are expected in emerging applications. This work will enable the development of a multitude of technologies that can improve the life of society-at-large. For example, this work can support the next generation of communication technologies for large-scale Internet of Things (IoT) applications and autonomous vehicle applications. Moreover, education is a core component of this project. New theories and algorithms developed in this project are integrated into the graduate-level courses at the three universities. Undergraduate and graduate students are involved in the project through the undergrad capstone and masters graduation projects at the Ohio State University.
This project explores the fundamental energy and spectrum-efficiency tradeoff of distributed spectrum access methods, and develops adaptive and correlated strategies that embrace and control randomness with efficiency guarantees for dynamic users with delay-sensitive traffic. In addition, the design incorporates humans into the loop by observing how humans react in simple multi-access games, providing simple human behavior models and simple human-perceived quality metrics, and by designing methods that can adapt to unexpected events or actions. A combined analysis and implementation approach of this project exploits high-dimensionality in the system while also overcoming difficulties for large-scale implementation and testing. In particular, the project develops mean-field techniques and analyses for large-scale spectrum access. Novel real-world experimentation strategies developed in this project emulate large-scale system operation in a small testbed by utilizing the simplification due to our randomized solutions and the integration of the aforementioned mean-field methods.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.OHIO STATE UNIVERSITY, THEOhio State UniversityAtilla Eryilmaz(614) 292-3732eryilmaz.2@osu.eduIrem Eryilmaz09/17/2018$250,034$250,03410/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITSpecEES: Collaborative Research: Leveraging Randomization and Human Behavior for Efficient Large-Scale Distributed Spectrum Access1824337832127323001964634SpecEES Spectrum Efficiency, EMonisha Ghosh(703) 292-8746mghosh@nsf.govOffice of Sponsored ProgramsColumbusOH43210-1016ColumbusUS03The Ohio State University2015 Neil Ave.ColumbusOH43210-1272ColumbusUS03An explosion of low-cost wireless devices promises new applications and services in diverse domains, including health, transportation, energy, manufacturing, and entertainment. This project focuses on developing energy and spectrum-efficient, distributed multi-access strategies for dynamic and large-scale wireless networks under the stringent energy and delay requirements that are expected in emerging applications. This work will enable the development of a multitude of technologies that can improve the life of society-at-large. For example, this work can support the next generation of communication technologies for large-scale Internet of Things (IoT) applications and autonomous vehicle applications. Moreover, education is a core component of this project. New theories and algorithms developed in this project are integrated into the graduate-level courses at the three universities. Undergraduate and graduate students are involved in the project through the undergrad capstone and masters graduation projects at the Ohio State University.
This project explores the fundamental energy and spectrum-efficiency tradeoff of distributed spectrum access methods, and develops adaptive and correlated strategies that embrace and control randomness with efficiency guarantees for dynamic users with delay-sensitive traffic. In addition, the design incorporates humans into the loop by observing how humans react in simple multi-access games, providing simple human behavior models and simple human-perceived quality metrics, and by designing methods that can adapt to unexpected events or actions. A combined analysis and implementation approach of this project exploits high-dimensionality in the system while also overcoming difficulties for large-scale implementation and testing. In particular, the project develops mean-field techniques and analyses for large-scale spectrum access. Novel real-world experimentation strategies developed in this project emulate large-scale system operation in a small testbed by utilizing the simplification due to our randomized solutions and the integration of the aforementioned mean-field methods.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MEMPHIS, THEUniversity of MemphisSantosh Kumar(901) 678-2487skumar4@memphis.edu09/17/2018$751,014$751,01410/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research1823221055688857878135631COMPUTING RES INFRASTRUCTURETonya Smith-Jackson(703) 292-5179tsmithja@nsf.govAdministration 315MemphisTN38152-3370MemphisUS09University of MemphisTN38152-3370MemphisUS09The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.
MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.GEORGIA TECH RESEARCH CORPORATIONGeorgia Tech Research CorporationJames Rehg(404) 894-9105rehg@cc.gatech.edu09/17/2018$225,000$225,00010/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research1823201097394084097394084COMPUTING RES INFRASTRUCTURETonya Smith-Jackson(703) 292-5179tsmithja@nsf.govOffice of Sponsored ProgramsAtlantaGA30332-0420AtlantaUS05Georgia Institute of Technology225 North Avenue, NWAtlantaGA30308-0002AtlantaUS05The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.
MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MARYLANDUniversity of Maryland College ParkShihab A Shamma(301) 405-6842sas@isr.umd.eduCarol Y Espy-Wilson09/17/2018$851,674$851,67410/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITRI: Medium: Neuromorphic and Data-Driven Speech Segregation1764010790934285003256088ROBUST INTELLIGENCEKenneth C. Whang(703) 292-8930kwhang@nsf.gov3112 LEE BLDG 7809 Regents DriveCOLLEGE PARKMD20742-5141College ParkUS05University of Maryland College ParkAV Williams BldgCollege ParkMD20742-3285College ParkUS05This project investigates how neural representations of speech and music in the cortex can be adapted and applied to overcome the challenge of robust perception in extremely noisy and cluttered environments, mimicking processing and capabilities of the brain. More specifically, the project will formulate algorithms inspired by the architecture of the brain to segregate and track targeted speakers or sound sources, test their performance, and relate them to state-of-the-art approaches that utilize deep artificial neural networks to accomplish these tasks. Human psychoacoustic and physiological experiments with these algorithms will be conducted to test the validity of these ideas for mimicking human abilities. This effort will spur the development of new neuromorphic computational tools modeled after the brain and its cognitive functions. In turn, these will provide a theoretical framework to guide future experiments into how complex cognitive functions originate and how they influence sensory perception and lead to robust behavioral performance.
The planned projects will be organized into two flavors. The first attempts to borrow from existing neuromorphic approaches that rely on cortical representations to develop new embeddings within the deep neural networks framework, which will in turn endow the latter with brain-like robustness in challenging unanticipated environments. Three specific efforts within this flavor will be conducted: Learning DNN embeddings using cortical representations of speech and music, exploring unsupervised clustering of cortical features using adversarial auto-encoders, and exploiting pitch and timbre representations to enhance segregation of sound. The second flavor of projects borrows from the DNN approach to build into neuromorphic algorithms the desirable performance and flexibility attained by training on available databases. Two broad areas of studies are planned: one focuses on questions of neuromorphic implementations that benefit from DNN toolboxes and ideas, especially in segregation and reconstruction. The other focuses on investigating how autoencoders can be exploited to implement feature reduction and clustering efficiently.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF COLORADO, THEUniversity of Colorado at BoulderJoshua J Tewksbury(206) 616-2129jote0936@colorado.edu09/17/2018$1,170,792$372,72510/01/201809/30/2021GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Core Support for the U.S. Hub of the Future Earth Secretariat1758001007431505007431505COLLABORATIVE RESEARCHAnne L. Emig(703) 292-8710aemig@nsf.gov3100 Marine Street, Room 481BoulderCO80303-1058BoulderUS02University of Colorado Boulder3100 Marine, Room 457BoulderCO80303-1058BoulderUS02This award provides core support for the staff and activities of the US Hub of Future Earth Secretariat. The Future Earth program seeks to coordinate international global change research to help accelerate transformations to sustainability through research and innovation. In this role, the US Hub of Future Earth serves as a convener that helps US researchers engage in research based on the co-design and co-production of knowledge and tools designed to help develop solutions to global environmental challenges such as fresh water security, coastal vulnerability, disaster risk reduction and resilience. The program is supported by major U.S. agencies, under the interdisciplinary auspices of the U.S. Global Change Research Program. Over the past several years, the US Hub has taken on activities that directly support the USGCRP and its member agencies. These funds will be used to further engage the US research community in these developing efforts.
The Future Earth program is organized around three major themes: Dynamic Planet; Global Development; and Transformations toward Sustainability. Under the auspices of these three themes, the US Hub of the Future Earth Secretariat will support workshops and other efforts to foster the co-design of research to enhance transdisciplinary efforts to help develop solutions for many challenging societal issues. The US Hub will also develop programs and initiatives to educate the next generation of inter-disciplinary researchers and professionals on how to integrate global sustainability with human prosperity and will actively engage the public through an extensive communication and outreach effort.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF BOSTON UNIVERSITYTrustees of Boston UniversityYves Atchade(734) 764-1817yvesa@umich.edu09/17/2018$221,874$221,87407/01/201806/30/2019GrantNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITHigh-Dimensional Bayesian Computations: The Moreau-Yosida Posterior Approximation1854545049435266049435266STATISTICSGabor J. Szekely(703) 292-8869gszekely@nsf.gov881 COMMONWEALTH AVEBOSTONMA02215-1300BostonUS07Trustees of Boston UniversityMA02215-1300BostonUS07Bayesian inference is a powerful statistical inference method that allows statisticians and other scientists to combine existing knowledge with new data samples for better inferences and decisions. The difficulty of sampling from posterior distributions is one of the biggest impediments to a wider adoption of Bayesian procedures in high-dimensional/big data analysis. There is a need for fast and accurate posterior approximation methods to assist with the practical implementation of Bayesian statistics in high-dimensional problems. This research project will use ideas from the related field of optimization to develop a Bayesian posterior approximation method that satisfies these requirements. The methodology will find applications in a wide-range of areas such as finance, marketing science, epidemiology, biology, medical sciences, and others.
More specifically, there is a need in statistics for posterior approximation methods in high-dimensional problems that: (a) produce approximations that are easier to explore by Markov Chain Monte Carlo (MCMC), and (b) are well-understood from a theoretical viewpoint. This project will use the Moreau-Yosida approximation and related tools from optimization and variational analysis to develop a Bayesian posterior approximation method that satisfies the above two conditions. The research from this project will help clarify similarities and differences between optimization and simulation problems. This research will also contributes to the theoretical analysis of Markov Chain Monte Carlo algorithms, with the special focus on understanding the mixing time of MCMC algorithms in high-dimensional settings. The project will also address open problems in high-dimensional Bayesian variable selection and will develop some novel modeling and computational solutions. There are many applied research areas, including biomedical research, epidemiology, marketing science, and social science research, where variable selection plays an important role. Hence, results from this research will allow researchers in those areas to better handle available data and gain new insights into relevant scientific questions. On the educational side, the material from this research will form a key component of the doctoral dissertation of the Ph.D. students supported by this grant. The project will also enable the PI to use the related scientific problems and datasets to enrich the learning experience of students in his classes and possibly other classes taught by his colleagues. Furthermore, novel methodologies from this research will be widely disseminated to the scientific community through presentation of academic seminars as well as presentations at high-visibility conferences in statistical computing.REGENTS OF THE UNIVERSITY OF COLORADO, THEUniversity of Colorado at BoulderRichard Eastes(303) 735-7221Richard.Eastes@lasp.colorado.edu09/17/2018$197,602$131,74308/01/201807/31/2020GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Laboratory Measurements of O and N2 Ultraviolet (UV) Cross Sections by Particle Impact for Remote Sensing of Thermosphere O/N2 Variation1853618007431505007431505AERONOMYJohn W. Meriwether(703) 292-8529jmeriwet@nsf.gov3100 Marine Street, Room 481BoulderCO80303-1058BoulderUS02University of Colorado at BoulderBoulderCO80303-1058BoulderUS02This award would advance the capabilities for UV remote sensing by targeting a laboratory goal, which is centered on the determination of the UV emission cross sections (Qem) needed for remote sensing observations of the Earth's dayglow. In the dayglow a unique signature of the O/N2 density ratio, from satellite-based UV observations, comes from measuring the intensity ratio of the OI (135.6 nm (3P2-> 5So2)) and N2 Lyman-Birge-Hopfield (LBH) band (125-250 nm) emissions. This O/N2 density ratio is a key to understanding the ionosphere and thermosphere composition changes on a global scale under all geomagnetic conditions. However, the total emission cross sections of these two sets of spectral transitions have not been measured. Each of these two total emission cross sections is a sum of a direct excitation emission cross section and a cascade cross section. The cascade cross sections are about 30-50% of the total cross section. As the column density ratio O/N2 plays a key role in Space Weather studies, accurate absolute measurements of Qem for both OI and LBH emissions are vital for explaining both the magnitude and temporal evolution of thermosphere composition (O/N2) changes. Similarly, the energetic proton (H+) and H atom impact laboratory measurements of Qem needed for auroral remote sensing are inadequate. The main focus of this is two-fold. One graduate student (UCF) and one undergraduate student would be supported in this effort.
The first goal of the award project would be to measure the absolute direct electron, H+, and H impact Qem for both the LBH band between 125 nm to 250 nm and OI (3P2-->5So2) at 135.6 nm from their emission thresholds to 500 eV by electron-impact, to 50 keV by H+ and H atom impact, using the team's experimental facilities located at Caltech/JPL. The team would also measure at the University of Colorado the cascade processes from these upper states. Aeronomers at the University of Central Florida (UCF) and Computational Physics Inc. (CPI) would model the remote sensing data using two classic particle transport codes that are paramount to the US space mission: AURIC and GLOW.UNAVCO, INCUNAVCO, Inc.Meghan Miller(303) 381-7514Meghan@unavco.orgCharles M Meertens, Glen S Mattioli, Donna Charlevoix09/17/2018$59,326,057$11,400,00009/01/201808/31/2023Cooperative AgreementsNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITEnabling Discoveries in Multiscale Earth Ssystem Dynamics: Geodetic Facility for the Advancement of Geoscience (GAGE) - EAR Scope1851159142357032GAGERussell C. Kelz(703) 292-4747rkelz@nsf.gov6350 Nautilus Dr.BoulderCO80301-5394BoulderUS02UNAVCO6350 Nautilus DriveBoulderCO80301-5394BoulderUS02UNAVCO will develop, operate, and maintain a distributed, multi-user Geodetic Facility for the Advancement of GEoscience (GAGE). Geodesy characterizes the Earth's time varying shape, orientation in space, mass distribution, and gravity field. It has revolutionized the geosciences, by measuring Earth changes with unprecedented spatial and temporal resolution. The GAGE facility employs expert professional staff, with guidance provided by the scientific community, to manage and operate a set of foundational geodetic capabilities that are essential for current research support, as well as frontier geodetic activities that will enable future research. The facility will promote advances in our understanding of continental deformation; tectonic plate boundary processes; the processes that drive earthquakes, volcanic eruptions and landslide hazards; continental water storage, atmospheric, ice sheet and glacier dynamics; and interactions among these components of the Earth system. The geodetic capabilities provided through the GAGE facility contribute to issues of national/global strategic importance, including geohazard assessment and disaster resilience; environmental management and economic development; and STEM (science, technology, engineering, and mathematics) education and workforce development. Data products from GAGE will be used by federal agencies including the National Aeronautics and Space Administration, the United States Geological Survey and the National Oceanic and Atmospheric Administration, for missions including spacecraft positioning, satellite orbit, and timing corrections; earthquake, tsunami, and volcano early warning; weather forecasting; water resources; and environmental management. State departments of transportation will use GAGE data to help support traffic monitoring and control and increasingly GAGE data will support commercial sector positioning needs including for agriculture, construction and surveying, transportation (including air, rail, and maritime), mining and resource exploration, and fleet vehicle tracking.
The GAGE facility will manage and operate: 1) global and regional continuously operating Global Navigational Satellite Systems (GNSS) and complementary geodetic technology networks; 2) portable geophysical instrumentation for use in principal investigator driven and community experiments; 3) geodetic instrumentation testing and support service; 3) data management systems for the collection, quality assurance, curation, management, and distribution of open access data and data products; and 4) education, workforce development, and public outreach programs that foster the development of the next generation geosciences workforce, are designed to be inclusive and enhance participation of traditionally underrepresented groups in the geosciences, and engage the public by highlighting advances in geophysical sciences and their societal relevance. Innovative and transformative research that will benefit from GAGE examines both the dynamics of individual processes and the nonlinear interactions within and among larger Earth systems. The study of active processes from geocenter motion to the studies of the lithosphere, cryosphere, hydrosphere, and atmosphere requires understanding of the coupling and feedbacks across a range of length and time scales, and between the solid Earth and its fluid envelopes, in both physical and biological environments. Under NSF, and NASA partner agency support for GAGE, UNAVCO will integrate and federate a set of currently operated but at present independently managed GNSS stations to form the Network of the Americas (NOTA). UNAVCO will modernize NOTA stations with state-of-the-art, multi-sensor, multi-GNSS, receivers with real-time streaming data and analysis. These enhancements will enable higher precision positioning than currently possible and new application of GNSS data that can be used for geohazards warning systems, study of ocean and atmosphere dynamical behavior, and observation of key environmental parameters such as water storage, soil moisture, and sea and lake-level changes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MATERIALS RESEARCH SOCIETYMaterials Research SocietyMONICA JUNG DE ANDRADE(469) 203-2286mxj105120@utdallas.eduJ. Ardie Butch Dillen09/17/2018$10,270$10,27011/01/201804/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSymposium: Nanomaterials and Nanomanufacturing for Sustainability; 2018 Materials Research Society Fall Meeting; Boston, Massachusetts; 25-30 November 20181846628107328510NANOMANUFACTURINGKhershed Cooper(703) 292-7017khcooper@nsf.gov506 KEYSTONE DRWarrendalePA15086-7573WarrendaleUS12Materials Research Society506 Keystone DrWarrendalePA15086-7573WarrendaleUS12This award is for the partial support for the Nanomaterials and Nanomanufacturing for Sustainability Symposium at the Fall Materials Research Society (MRS) Meeting in Boston, Massachusetts, 25-30 November 2018. The award provides funds for the conference travel and registration expenses of graduate students, postdocs, early career faculty, and underrepresented minority and women researchers. The MRS Meeting is the premier international conference, where academic, government laboratory and industry representatives participate, speak and discuss topics in advanced materials and manufacturing. This Symposium's topic is Sustainable Nanotechnology, with a specific focus on Nanomaterials and Nanomanufacturing. The Symposium advances knowledge in in emerging and advanced nanomaterials and nanomanufacturing for sustainability and environment, which impacts the nation's prosperity and health. The Symposium is a networking and workforce development opportunity by providing a forum for students and young faculty to meet attendees from industry, government labs and other academic institutions.
The Nanomaterials and Nanomanufacturing for Sustainability Symposium's goal is to advance knowledge in emerging and advanced nanomaterials and nanomanufacturing for cleaner, more efficient technologies for transportation, energy management, environmental monitoring and depollution. The topics are nanomaterials and nanomanufacturing for sustainability; air, soil and water quality management; renewable energy; lighter and stronger materials; nanotoxicology; and life cycle analysis. The symposium is a venue for tutorials, keynote lectures, oral and poster presentations, and networking for students, faculty and industry. It is a forum to learn new methods and exchange research results. A novel sub-event involves rapid-fire presentations to give an opportunity to all poster presenters to pitch their poster for 1 minute during the oral sessions and on a LCD screen next to the outside signage of the session. Winning pitches are recognized.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF ROCHESTERUniversity of RochesterQiang Lin(585) 275-4031qiang.lin@rochester.eduHui Wu, Lin Zhu09/17/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: A high-speed, reconfigurable, fully integrated circuit platform for quantum photonic applications1842691041294109041294109COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov518 HYLAN, RC BOX 270140RochesterNY14627-0140RochesterUS25University of RochesterRochesterNY14627-0127RochesterUS25RAISE-EQuIP: A high-speed, reconfigurable, fully integrated circuit platform for quantum photonic applications
Quantum photonics utilizes the intriguing quantum characteristics of photons for information processing. Fast manipulation and transformation of photonic quantum states at a high speed underlie crucially the capability and capacity of quantum communication and computing. However, to date, it remains an open challenge to do so, which becomes a bottleneck for the speedup of photonic quantum information processing. On the other hand, current integrated quantum photonic circuits rely seriously on external off-chip laser sources for proper operation, which becomes a major obstacle limiting the integration and miniaturization of quantum photonic circuits which in turn limits the degree of functional complexity they can offer. The proposed research aims to address these challenges. With the synergetic research effort of our team, we propose to focus on innovative circuit- and system-level engineering to build large-scale fully-integrated quantum photonic circuit systems that can be flexibly reconfigured and modulated at high speed, aiming to achieve novel quantum functionalities with unprecedented functional complexity inaccessible to other means.
The proposed research covers all three thrusts of the EQuIP program. With our proposed research, we envision an entirely transformative avenue towards integrated quantum photonics that may ultimately revolutionize the state of the art of communication and information processing, advancing its maturity level towards practical implementation that would have significant impact on industrial sectors. The proposed research offers comprehensive training in the diverse interdisciplinary areas of quantum and integrated photonics, high-speed RF circuitry, electronic circuit design, lasers, and signal processing, to prepare workforces for future quantum engineering industry. It will also result in promoting the interest and participation of K-12 students and broadening the participations from underrepresented groups, through outreach programs.
The proposed research aims to explore and develop high-speed, flexibly reconfigurable, fully integrated quantum photonic circuits that offer unprecedented capability of manipulating, translating, and transducing photonic quantum states, encoding/decoding and processing quantum information. To this end, we have assembled a multidisciplinary team of leading experts with strong expertise and extensive experience in quantum photonics, nanophotonics, optoelectronic integration, high-speed RF circuitry, electronic IC design, semiconductor lasers, hybrid optoelectronic integration, to propose a fundamental research effort directed at the realization of scalable high-speed hybrid quantum photonic circuit systems that perform significantly beyond the reach of single individual components. The proposed research will integrate elegantly the outstanding and unique properties of underlying material platforms with innovative circuit and system design and engineering and laser-chip integration to realize very high speed modulation, tuning, and reconfiguration of large-scale integrated quantum photonic circuits that would enable novel quantum photonic functionalities with unprecedented functional complexity and capability. The preliminary results show great promise to achieve these goals. The strong expertise and extensive experiences of our team position us uniquely for the proposed research project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.JOHNS HOPKINS UNIVERSITY, THEJohns Hopkins UniversitySuchi Saria(410) 516-8668suchi.saria@gmail.comChien-Ming Huang, David Newman-Toker, William V Padula, Martin Makary09/17/2018$1,500,000$1,500,00001/01/201912/31/2023GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITFW-HTF: Human-Machine Teaming for Medical Decision Making1840088001910777001910777FW-HTF: Advancing Cognitive anMeghan Houghton(703) 292-8900mehought@nsf.gov1101 E 33rd StBaltimoreMD21218-2686BaltimoreUS07Johns Hopkins University3400 N CHARLES STBaltimoreMD21218-2608BaltimoreUS07The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by NSF. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. Algorithmic advances in artificial intelligence are transforming human work in diverse areas including transportation, finance, national security, and medicine. Machine intelligence presents opportunities to increase human work productivity and the quality of jobs through augmenting human capabilities. Effective teaming between humans and intelligent machines similar to effective human-human teamwork has the potential to yield significant near-term gains. This project explores the challenges of human-machine teaming in medical decision making. Health care is one of the most difficult challenges that the United States is facing. The US spends $3 trillion dollars in health care each year, while medical error is the third leading cause of death. Human-machine cognitive teaming creates a new model of patient care in which providers team with intelligent cognitive assistants to enhance quality of care under time pressure, taxing workloads, and uncertainties in medical conditions. This project explores the potential for effective human-machine teaming to mitigate such challenging problems in health care.
Specifically, this project seeks to understand (1) whether human-machine teaming can benefit medical decision making and decision making in other related high stakes domains; (2) the guiding principles for designing effective human-machine teams; (3) barriers that currently exist for building such teams; (4) novel solutions needed to address barriers in order to develop highly performant teams; and (5) the economic and societal impacts of the planned approach for human-machine teaming. Understanding effective human-machine teaming, including the broader implications in the workspace and in human workflows, will contribute to positive transformation of human work. In particular, it is anticipated that the outcomes of this project will result in improvements in hospital utilization and reduction of medical errors. The project integrates multiple disciplinary perspectives, including computer science, medical expertise, health policy, and decision making. The impacts of the research will extend to multiple hospitals in the Baltimore region. Furthermore, the project will engage local high school students in summer research experiences, and the outcomes of the research will be integrated into undergraduate curricula.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MOREHOUSE COLLEGE (INC.)Morehouse CollegeKinnis Gosha(470) 639-0634kinnis.gosha@morehouse.edu09/17/2018$299,621$299,62101/01/201912/31/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITPairing Atlanta High School Teachers with HBCU Computer Science Students to Train Them on AP Computer Science Principles1837541075861773075861773STEM + Computing (STEM+C) PartJanice E. Cuny(703) 292-8489jcuny@nsf.gov830 Westview Drive S WAtlantaGA30314-3773AtlantaUS05Morehouse College830 Westview Drive, S.W.AtlantaGA30314-3773AtlantaUS05Morehouse College proposes to explore outcomes of a novel teacher professional development (PD) program that prepares in-service high school teachers to teach the Advance Placement Computer Science Principles (AP CSP) course, the Beauty and Joy of Computing (BJC), with support from undergraduate computer science (CS) majors. The work leverages longstanding relationships between members of the Atlanta University Center Consortium (Morehouse College, Spelman College, and Clark Atlanta University), and the Atlanta Public Schools (APS). APS predominantly serves and employs African American and other minority students and teachers. Likewise, the Historically Black Colleges and Universities (HBCUs) of the Atlanta University Center primarily serve minority undergraduate students. Through this unique model, minority in-service, high school teachers will receive BJC professional development and support from minority undergraduate CS students in teaching their majority-minority AP CSP classes. The undergraduates will serve both as teaching assistants for the new CS teachers and as role models for the students. In turn, minority APS students will receive rigorous CS instruction made relevant and contextualized within their culture.
This project will study the effects of in-person undergraduate teaching assistants during PD for and implementation of the BJC curriculum within minority populations. It will examine the outcomes of these teaching assistant/teacher relationships, examining changes in teachers' CS content knowledge, understanding of careers in computing, confidence in teaching CS, and success in recruiting and retaining students of color. Likewise, it will examine effects on the undergraduate student teaching assistants in terms of ability to provide instructional support, levels of civic engagement, CS content knowledge, and professional identity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.THE GEORGE WASHINGTON UNIVERSITYGeorge Washington UniversityGabriel A Parmer(202) 994-9741gparmer@gwu.eduTaeyoung Lee Dr, Timothy Wood Dr.09/17/2018$1,000,000$1,000,00001/01/201912/31/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: Medium: Edge-Cloud Support for Predictable, Global Situational-Awareness for Autonomous Vehicles1837382043990498043990498CYBER-PHYSICAL SYSTEMS (CPS)Jonathan Sprinkle(703) 292-8719jsprinkl@nsf.gov2121 Eye Street NWWashingtonDC20052-2000US00George Washington University2121 Eye Street, NWWashingtonDC20052-0001WashingtonUS00The goal of this project is improved situation awareness for autonomous vehicles across many different networks. The approach is new theory and abstractions for systems where potentially moving physical systems join and leave the network at a high rate. Making these kinds of cyber-physical systems (CPS) efficient and safe requires leveraging the sensor information from other proximate vehicles over the network: this will enable vehicles to have much higher situational awareness--effectively seeing around corners. However, computation must be performed fast enough to accurately control the physical system, and coordination over networks makes this even more challenging. The research program is paired with an educational initiative integrated into the extensive mentoring program of the researchers, with an emphasis on involving students of diverse backgrounds.
This project investigates CPSEdge, a software platform deployed at the network "edge", which aggregates sensor information from nearby vehicles, and intelligently shares resulting plans of action. CPSEdge leverages its network proximity to vehicles, and is carefully designed to reply to vehicles fast enough to keep up with a quickly changing physical environment. The tools and techniques developed for CPSEdge will offer greater situational awareness to autonomous vehicles, and improve the responsiveness, reliability, and security of the software platforms that manage them. CPSEdge is built on a new process abstraction that is lightweight and can scale up to very large systems, even under significant churn, while providing increased reliability and security. This abstraction is managed by the CPSEdge system to ensure that the requisite computation is conducted in real-time with the physical system. Sensor data will be fused to generate a probabilistic model of the environment, providing global planning for nearby vehicles.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.NORTH CAROLINA AGRICULTURAL AND TECHNICAL STATE UNIVERSITYNorth Carolina Agricultural & Technical State UniversityHyung Nam Kim(336) 285-3471hnkim@ncat.edu09/17/2018$499,807$499,80710/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITExcellence in Research: Human Factors Approach to Facilitate Ambient Assisted Living Accessible and Usable to People with Visual Impairments: Loneliness Self-Monitoring System1831969071576482142363428I-CorpsM. Mimi McClure(703) 292-5197mmcclure@nsf.gov1601 E. Market StreetGreensboroNC27411-0001GreensboroUS06North Carolina Agricultural & Technical State University1601 E. Market StreetGreensboroNC27411-0001GreensboroUS06Excellence in Research awards provide support for faculty at Historically Black Colleges and Universities to strengthen their research capacity. The award to North Carolina Agricultural & Technical State University has potential broader impact in a number of scientific and societal areas. The project will utilize a user-centered design methodology to conduct research that analyzes the unique gait characteristics of visually impaired individuals in the home, with consideration for the use of assistive devices or service dogs. This gait analysis and human factors research will facilitate an understanding of subjective factors, emotional status and aloneness for these visually impaired individuals. Finally, the research outcomes will support self monitoring such that the end users can be informed about the loneliness detection and assessment results through the use of accessible formats (e.g., voice user interfaces). This research benefits the visually impaired, supports educational opportunities for students and advances knowledge in the use of human centered design research to address unique needs of those individuals with disabilities.
The project is an ergonomics/human factors study that utilizes health informatics and data analytics to focus on advancing knowledge, technology, and human factors engineering principles to accurately assess human behavioral data in a natural environment (i.e. the home). The focus is on analytical modules specifically designed for the inclusion of persons with disabilities (i.e. visual impairments). The project objectives include conducting a user-centered contextual inquiry in a natural environment, developing the data collection, analysis, and report modules for the system using an iterative user-centered design approach, and finally, assessing the validity, reliability, and usability of the proposed system in an individual's natural environment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.BETA HATCH INC.Beta Hatch IncVirginia J Emery(510) 292-9231virginia@betahatch.com09/17/2018$630,632$630,63209/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Scalable insect farming for agriculture1831538079938555SMALL BUSINESS PHASE IIAnna Brady-Estevez(703) 292-7077abrady@nsf.gov1421 S 192nd StreetSeaTacWA98117-2328SeattleUS07Beta Hatch Inc1421 S 192nd StreetSeaTacWA98148-2328SeatacUS09The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project are foundations for an emerging industry: insects in agriculture. Beta Hatch is pioneering the production of new animal feed ingredients, developing technology to mass produce insects, and creating STEM jobs. The proposed work will allow scaling insects as a sustainable protein-rich feed ingredient. With predictable year-round production, this will contribute to a more robust and secure agricultural system. The Beta Hatch insect ranch, which will be designed through integration of the results from this project, is an on-site solution to convert organic by- products into valuable feed ingredients and fertilizer. These ranches are being designed as conversions of underutilized spaces (warehouses and poultry barns), to bring jobs to rural and HUBZone areas. We work closely with farmers, our main customers, to establish the performance and economic value of our products. Insects provide nutrition and make animals healthier. Our frass (insect manure), is an organic fertilizer that stimulates healthy soils, and has no nitrates (no runoff). The proposed work will allow us to establish insects as the world?s most sustainable animal feed ingredient, and to disrupt the $400B animal feed market.
This SBIR Phase II project proposes to cost effectively scale insect production for agricultural markets. Of the millions of insect species that exist, only a handful have been successfully reared under controlled conditions and even fewer have been mass produced. And yet insects have the potential to fill essential roles in agricultural supply chains by biodegrading wastes, removing or recycling toxins, and providing nutrition for animals. In order to meet the scale, quality and cost requirements for agricultural markets, significant R&D must solve some core challenges in insect mass production. We propose to integrate biological and engineering approaches to develop novel oviposition substrates, identify and mitigate causes of mortality, design automated and flexible diet handling systems, optimize rearing trays (the basic unit of production), and maximize yields with automated water and diet delivery. The proposed work will cut over 80% of our costs, produce several patents, and inform the design of a scalable insect ranching facility. As a natural part of animal diets, insects are a predictable protein-rich alternative feed ingredient, with year-round controlled production. In Phase 1 of this project, we established an insect breeding program, explored novel inorganic diets, and identified the core production challenges for scaling insects-as-feed. For this NSF SBIR Phase 2 project, we develop solutions that will reduce the cost of production and control the cost of future facilities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.IMAGEN ENERGY LLC.Imagen Energy, LLCJason Katcha(414) 704-0274jason@imagenenergy.com09/17/2018$626,856$626,85609/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Extremely Compact, High Efficiency, Integrated Converter and Energy Storage System1831221080282639SMALL BUSINESS PHASE IIMuralidharan S. Nair(703) 292-7059mnair@nsf.gov15230 W. Woodland Dr.New BerlinWI53151-1915New BerlinUS05Imagen Energy LLC115 E Reindl Way, Suite 295MilwaukeeWI53212-1255MilwaukeeUS04The broader impact/commercial potential of this project is to enable vast deployment of energy storage to increase installation of renewable energy for reduced pollution and greenhouse gases, to improve energy security, and to improve energy efficiency and safety. The project will realize a dramatic reduction in cost and size of Energy Storage Systems (ESS) that will allow penetration of ESS into markets served by fossil fuels. One key market is grid ancillary services which includes Frequency Regulation (FR) that regulates grid frequency and stability. With the potential of this project, the FR market for battery based ESS is expected to grow from $100M/yr to over $4B/yr. This project has the societal benefits of replacing fossil fuel based ?peaker? plants that are commonly used to perform FR, with clean Li-ion battery based ESS. Furthermore, by providing lower cost FR capability for the grid, the project will enable grid penetration of more renewable energy, which requires additional FR capability.
This Small Business Innovation Research (SBIR) Phase II project will develop a highly compact integrated modular inverter/energy storage system to revolutionize deployment of energy storage system for grid, micro-grid, energy efficiency, and energy reliability support. The development effort proposed here includes an advanced energy storage system consisting of an extremely compact 150kW high frequency 3-level inverter, an integrated 100kWhr compact Li-ion battery system, proprietary battery management systems and internet communications capability. This will provide a highly integrated and scalable 150kW Energy Storage System with an integrated battery string inverter with 60% reduced system cost and 10X reduced size that will open new markets for energy storage and renewable energy. The project will develop key technology innovations which work together with advanced Li-ion batteries to form a revolutionary new product. These innovations include: high frequency 3-level inverter with innovative high frequency control and output filter to achieve >10X reduction in volume; a novel topology that integrates inverters into each cell string and eliminates many components resulting in 60% system cost reduction; a modular and scalable design that is fault tolerant and allows easy optimization for multiple system uses.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TG COMPANIES, LLCTG Companies, LLCCoby S Tao(817) 965-2561cobytao@tg-companies.com09/17/2018$732,880$732,88009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Profitable Recycling of Silicon Solar Cells and Modules1831148078696112SMALL BUSINESS PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov16038 E Tumbleweed DrFountain HillsAZ85268-0000US06TG Companies, LLC551 E Tyler MallTempeAZ85281-0001TempeUS09The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to make the 'green' solar industry truly green. As the deployment of solar modules expands rapidly, so will module wastes. The International Renewable Energy Agency (IRENA) estimates that module wastes will appear in large quantities by early 2030's and by 2050 they will total 78 million tonnes. Today most module wastes end up in landfills. This SBIR project will develop a technology to maximize the revenue from module recycling. It has the potential to enable a profitable recycling business without any government subsidy. By recovering all the valuable components in modules, our technology has the potential to generate up to $60 billion in revenue from 78 million tonnes of modules.
The proposed project develops sustainable recycling processes and related equipment for silicon solar cells and modules. The goal of the project is to separate and recover all the valuable, toxic, and bulky components in cells and modules including solar-grade silicon, silver, lead, copper, aluminum, tin, and glass. The target for solar-grade silicon recovery is 85% and the target for metal recovery, especially silver, is over 90%. The revenue from recycling, based on today's prices for solar-grade silicon and silver, is $15/module by our technology, as compared to $3.50/module by today's technology. The primary work of this project will be developing a prototype for silicon solar cell recycling and optimizing the process for a production environment. The target throughput of the prototype is up to 50 kg of solar cell wastes per day.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.AZIMUTH1, LLCAzimuth1, LLCJason R Dalton(703) 618-8866jason.dalton@azimuth1.com09/17/2018$750,000$750,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Envimetric - Soil and water contamination predictive modeling tools1831137063710978SMALL BUSINESS PHASE IIAnna Brady-Estevez(703) 292-7077abrady@nsf.gov501 Church St NEViennaVA22180-4711ViennaUS11Azimuth1, LLC1751 Pinnacle Dr, Suite 600McLeanVA22102-4007McLeanUS11The broader impact/commercial potential of this Small Business Innovative Research (SBIR) Phase II project is a significant reduction in the cost and time to remove hazardous contaminants from the soils and groundwater impacting communities.
Properties observed from thousands of contaminated sites serve as inputs to a computerized mathematical model of the site, forecasting the most likely shape and depth of a contaminant plume. This machine learning model gives remediation planners access to a fast delineation of volume to be remediated as well as the uncertainty of the modeled estimate. This saves time and money searching for these contaminants that are deep underground and in groundwater. This Phase II project will expand on the Phase I prototype, creating an operational product capable of reaching the needs of environmental engineers and scientists around the globe, providing the stimulus to cut remediation time and cost in half.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.CODECRAFT WORKS, LLCCodecraft Works, LLCRahul Thawal(321) 419-5725rthawal@codecraftworks.com09/17/2018$741,395$741,39509/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: A Co-creation, Cross-curricular, Standard Aligned Computer Science, Engineering, and Cybersecurity Education Technology Platform1831060063220210063220210SMALL BUSINESS PHASE IIRajesh Mehta(703) 292-2174rmehta@nsf.gov407 Riverview LaneMelbourne BeachFL32951-2716Melbourne BeachUS08Codecraft Works, LLC2428 Irwin StreetMelbourneFL32901-7316MelbourneUS08This SBIR Phase II project aims to transform the lives and future economic opportunities of young people and their communities through democratized access to cross-curricular computer science, engineering, and cybersecurity education. Daily life, economies, innovation, and national security all depend on having a strong and skilled STEM workforce. For this workforce to exist, our schools must provide the necessary education and experience to prepare students for such careers. Unfortunately, a vast majority of K-12 educators today are not equipped with the resources to do so successfully. The importance of solving this problem cannot be overstated; developing a plentitude of competent STEM professionals is critical to ensure economic and security stability. These project goals are aligned with NSF?s mission to promote the progress of science; to advance the national health, prosperity, and welfare; and to secure the national defense. The resulting technology innovation is of potential service to more than 50 million primary and secondary school students and 3.5 million educators nationally, with an ability to impact their course of study, improve STEM outcomes, increase hands-on project-based experience, and improve future economic opportunities.
This technology innovation emerges at the intersection of cloud-based software technology, real-time collaboration tools, and learning management systems. This reimagined technology tool easily connects, attracts, and fosters delivery of cross-curricular, educational computing literacy resources aligned with national and state educational standards. The project aims to empower and support educators and students in tackling the many new opportunities and growing number of resources in computer science (CS) and engineering education at home, in classrooms, and in community centers. As the CS education landscape evolves with new and exciting technical curriculum, this innovation analyzes the willingness of educators to create or adopt new computer science education, the effectiveness of real-time collaboration tools on CS education outcomes, and measures student awareness and feelings about computer science and engineering disciplines. This technology innovation promotes customer participation and a unique ability to provide support at the ground level in real-time. There are solutions that provide massive online CS courses and curricula; however, none targeting K-12 classrooms or educators which support and integrate cross-curricular computer science, engineering, and cybersecurity education. Offering cloud-based, synchronous technology tools this technology enables real-time, expert mentoring and pair-programming in a K12 virtual learning environment on a massive scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF NOTRE DAME DU LACUniversity of Notre DameHai Lin(574) 631-3177hlin1@nd.edu09/17/2018$509,527$509,52710/01/201809/30/2022GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITNRI: INT: COLLAB: Interactive and collaborative robot-assisted emergency evacuations1830335824910376048994727National Robotics InitiativeRalph Wachter(703) 292-2653rwachter@nsf.gov940 Grace HallNOTRE DAMEIN46556-5708Notre DameUS02University of Notre Dame940 Grace HallNotre DameIN46556-5708Notre DameUS02Many emergencies require people to evacuate a building quickly. During an emergency, evacuees must make quick decisions, so they tend to rely on default decision making that may put them at risk, such as exiting the way they entered, following a crowd, or sheltering in place. When a crowd attempts to exit through a single exit, choke points and crowd congestion may impede the safe flow of evacuees, potentially resulting in a stampede of people and the loss of human lives. Mobile robots are increasingly being deployed as assistants on city streets and in hotels, shopping centers and hospitals. The future ubiquity of these systems offers an opportunity to change how people are evacuated from dangerous situations. In particular, when compared with traditional emergency infrastructure, such as fire alarms and smoke detectors, mobile robots can achieve better situation awareness and use this information to expedite evacuation and enhance safety. Additionally, mobile robots can be used in risky and life-threatening situations, such as chemical spills or active shooter scenarios, which present dangers to human first responders.
This project aims to derive a scalable design framework and develop an embodied multi-robot evacuation system where multiple mobile robots, originally tasked for different purposes, serve as emergency evacuation first responders leading people to safety. In particular, multiple mobile robots efficiently coordinate with each other and actively interact with evacuees to maximize their egress. The project significantly contributes to the understanding of how people respond to a robots' directions and authoritative commands. Furthermore, the project implements these findings and demonstrates their effectiveness using real-world experiments with human subjects. Beyond emergency evacuation, the research findings can be extended to many other related areas, especially those involving cooperative robot teams that are embodied in an uncertain and dynamic physical world with the need to actively interact with humans; e.g., battlefield, law enforcement, urban transportation systems, manufacturing systems, rehabilitation and health management.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.FLORIDA INTERNATIONAL UNIVERSITYFlorida International UniversityElias A Alwan(305) 348-5424ealwan@fiu.eduOsama A Mohammed, John L Volakis, Stavros Georgakopoulos, Shubhendu Bhardwaj09/17/2018$559,997$559,99710/01/201809/30/2019GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITMRI: Acquisition of an 18GHz to 110GHz Millimeter-Wave Anechoic Chamber1828458071298814159621697MAJOR RESEARCH INSTRUMENTATIONAnil Pahwa(703) 292-2285apahwa@nsf.gov11200 SW 8TH STMiamiFL33199-0001MiamiUS26Florida International University10555 W Flagler St,MIAMIFL33174-1630MiamiUS25Fifth generation (5G) cellular and millimeter-wave (mm-wave) networks are expected to play a significant role in next generation communication and sensing systems. Indeed, mm-wave technology provides multi-Gigabit-per-second (Gbps) data rates to mobile and Internet-of-Things (IoT) devices, projected to grow to 200 billion by 2020. Currently, 5G/mm-wave research is very active. However, to effectively study, design, and characterize 5G/mm-wave systems, new state-of-the-art instrumentation is needed, traditionally not present in academic labs. The proposed instrumentation will provide unprecedented measurement and characterization capabilities of 5G/mm-wave antennas and devices. Therefore, it will enable Florida International University (FIU) to: (a) conduct current and future cutting-edge 5G/ mm-wave research projects, (b) develop novel 5G/mm-wave technologies for cellular networks, satellite and airborne communications, as well as brain studies and cancer diagnoses and treatments, (c) offer new opportunities to train post-docs, graduate, undergraduate, and K-12 students to become experts in high frequency radio frequency (RF) technologies, creating much needed national workforce in this area, (d) serve as a state-of-the-art technical hub in South Florida, attracting new statewide, national and international academic and industry collaborators, (e) foster new opportunities for cross-disciplinary and multi-institutional research, and (f) support the growth of a strong and diverse U.S. workforce in RF communication. Therefore, the proposed instrumentation will have significant impact in research, education, and technology development. This acquisition will further advance FIU's educational efforts to broaden participation of women and other underrepresented groups in STEM through curriculum development, REU programs, and outreach efforts.
The proposed instrumentation from Microwave Vision Group (MVG), called -Lab, is highly specialized and incorporates important requirements for compatibility and interoperability, across 18 GHz to 110 GHz. This instrumentation consists of an anechoic chamber equipped with absorbers, precision positioning control system, RF equipment modules (network analyzers, coaxial cables, waveguides, probes, etc.) and data post-processing. Different modules are required for different frequency bands viz. K (18-26 GHz), Ka (26-40 GHz), V (50-75GHz), and W (75-110GHz) bands. Research in the frequency range 18-110 GHz has so far been impeded by the lack of affordable testing equipment with large measurement inaccuracies. This is mostly due to the small footprint of related RF devices. As a result, research activities in related communications, biomedical, and other scientific fields have been so far limited to much lower frequency range. The procurement of such instrumentation will eschew traditional limitations often encountered with high frequency testing and characterization of future mm-wave, terahertz, and IoT components devices and systems. The broadband frequency (18-110GHz) offered by this instrumentation will enable groundbreaking and transformative research in RF communications with multi-Gbps data rates. Such capability will revolutionize a) cellular networks, b) airborne and satellite communication systems, c) vehicle-to-vehicle communications, d) reconfigurable and deployable RF systems, e) wearable and implantable devices, f) brain and cancer studies, g) terahertz and mm-wave cameras, h) terahertz sources and on-chip terahertz antennas, and i) secure communications among others. In summary, research in 5G and mm-wave technologies, which will be enabled by the proposed instrumentation, is expected to have great impact on information technology, telecommunications, diagnosis of diseases and biomonitoring, thereby improving quality of life and health.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF TUFTS COLLEGE INCTufts UniversityElena N Naumova(617) 636-2927elena.naumova@tufts.edu09/17/2018$100,697$100,69710/01/201809/30/2021GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITIRES Track I: Collaborative Research: U.S.-Indonesian Research Experience for Students on Sustainable Adaptation of Coastal Areas to Environmental Change1826939073134835073134835IRES Track I: IRES Sites (IS)Maija M Kukla(703) 292-8710mkukla@nsf.gov136 Harrison AveBostonMA02111-1817BostonUS07Tufts UniversityMA02111-1817BostonUS07This is a collaborative three year IRES project for 18 US students to gain international research experience in earth, life and data sciences as applied to the coastal region of Northern Central Java, Indonesia. The collaborative activities will be performed in partnership between Boston University (BU), Tufts University (TU) and the University of Diponegoro (UNDIP), Semarang, Indonesia. A cohort of six students per year will gain hands-on laboratory and field experience in coastal zone research during a six-week stay at the foreign institution.
Coastal cities worldwide are facing the enormous task to become resilient against physical, social and economic challenges, in addition to challenges due to climate variations. Semarang (Indonesia) is one of the cities that exemplifies the multiple threats affecting society, economy, environment, and infrastructure. Assessing the impacts of present and future coastal hazards requires an understanding of the complex interactions between geological, hydrological, biophysical and socioeconomic systems. This can be best achieved by an integrated approach that includes research on both land and sea dynamics to identify natural and anthropogenic factors, their relative influences and related consequences. This project seeks to undertake effective, innovative, and transformative research to understand how coastal environments respond to natural and anthropogenic factors. Geospatial technology combined with big data analytics will be applied to assessing and monitoring the effects of coastal hazards with the goal to enable the sustainable adaptation of coastal areas to global environmental change. Students will learn data acquisition techniques and the ability to analyze and interpret scientific information.
The proposed research will combine field experience with cutting edge geospatial technology and data analytics to investigate the following research questions:
1. Is land subsidence in Semarang coastal area mainly caused by natural or anthropogenic processes? Or both? How can we determine the prevailing factors; whether it is due to groundwater abstraction, tectonic movement, volcanic activities or a combination of factors?
2. To what extent is the marine productivity of coastal waters near Semarang city affected by changing climatologic conditions of oceanic and atmospheric parameters in Java Sea? How is climate variations impacting fisheries resources and the economic productivity of coastal communities? How can we build models that show the linkages?
3. How can we effectively monitor and assess coastal marine ecosystems health and productivity? Are artificial patch reefs and mangrove reforestation efforts in Semarang coastal region effective solutions for protecting and rehabilitating coastal ecosystems?
4. How can geospatial technology and big data analytics help in revealing crucial interactions between ecological, economic and policy aspects to assess and manage the environmental risks? How can we measure and assess the changes in food intake pattern and food safety in relation to extreme weather and coastal hazards?
This project will establish a long term collaborative research and training program between US and Indonesian faculty and students. US students majoring in STEM fields will have an opportunity to conduct research and field work in an international and multi-disciplinary setting by engaging in problem solving research activities. They will be mentored by foreign collaborators and US PIs through web video conferencing and workshops jointly taught at the collaborating institution. The IRES experience is expected to a) broaden and leverage partnerships with overseas institutions, b) enhance US-student global awareness and perspectives, and c) develop multi-disciplinary themes that improve understanding of global change such as coral bleaching, habitat diversity, and coastal hazards. Research findings will be disseminated through peer-reviewed publications and presentations at conferences. In partnership with UNDIP and relevant agencies in Northern Central Java region, decision support products resulting from this project will be distributed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF MASSACHUSETTSUniversity of Massachusetts AmherstBenjamin M Marlin(413) 545-4493marlin@cs.umass.edu09/17/2018$248,462$248,46210/01/201809/30/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCRI: CI-EN: Collaborative Research: mResearch: A platform for Reproducible and Extensible Mobile Sensor Big Data Research1823283153926712079520631COMPUTING RES INFRASTRUCTURETonya Smith-Jackson(703) 292-5179tsmithja@nsf.govResearch Administration BuildingHadleyMA01035-9450HadleyUS02University of Massachusetts AmherstMA01003-9264AmherstUS02The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) has developed open-source software for smart phones and cloud. Scientists use MD2K software to develop and test algorithms to monitor health, wellness, and work productivity via wearable sensors. The mResearch project is aimed at assisting Computer and Information Science and Engineering (CISE) researchers. The mResearch project will significantly enhance MD2K software and integrate Internet-of-Things (IoT) devices. The enhanced MD2K software will accelerate research in sensors design, mobile computing, privacy, analytics (especially machine learning and deep learning), and visualization. mResearch will enable CISE researchers to easily deploy their contributed software in scientific studies for health, smart homes, and workplace. The resulting discoveries and tools will help individuals improve their health, wellness, and work productivity.
MD2K has developed open-source mobile sensor big data software platforms mCerebrum for smartphones and Cerebral Cortex for the cloud. This scalable and generalizable infrastructure is used for collecting, analyzing, and sharing high-frequency, mobile sensor data and associated labels in the context of scientific field studies. In particular, it supports the development and validation of models and algorithms for inferring markers of health, wellness, and productivity, and their associated risk factors. It has already been used at eleven sites across the country to collect over 300 terabytes of mobile sensor data in the field setting from over 2,000 participants. It has resulted in new computational models for the detection of conversation, smoking, eating, craving, stress, and cocaine use. The mResearch project is making five significant infrastructure enhancements to the MD2K infrastructure to assist CISE researchers in mobile sensor development, mobile computing, privacy, analytics, visualization, and participant engagement. First, it will enable data analytic workflow management across multiple layers of the system to enable reproducible and extensible experimentation. Second, it will allow encapsulation of data sources to provide convenient and responsible access to them in data analytic workflows. Third, it will facilitate cloud-assisted complex, real-time analytics for personalizing mobile interventions and improving engagement. Fourth, simulators will be developed with the ability to feed stored data into the platform at various points to enable research on system components and properties such as data compression, transfer and storage, as well as the scalability of data analytics. Finally, Internet-of-Things (IoT) devices and services will be integrated. With these five enhancements, the MD2K software will provide a complete, open, and modularized architecture. It will include all aspects of sensor data collection, data processing algorithms, cloud-based machine learning, and IoT integration. The enhanced MD2K software will facilitate reproducible and extensible CISE research with high-frequency mobile sensor data.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.COLORADO STATE UNIVERSITYColorado State UniversityPeter Backlund(970) 491-6355peter.backlund@colostate.edu09/17/2018$1,197,704$387,49410/01/201809/30/2021GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Core Support for the U.S. Hub of the Future Earth Secretariat1758047785979618948905492COLLABORATIVE RESEARCHAnne L. Emig(703) 292-8710aemig@nsf.gov601 S Howes StFort CollinsCO80523-2002Fort CollinsUS02Colorado State University200 W. Lake StreetFort CollinsCO80521-4593Fort CollinsUS02This award provides core support for the staff and activities of the US Hub of Future Earth Secretariat. The Future Earth program seeks to coordinate international global change research to help accelerate transformations to sustainability through research and innovation. In this role, the US Hub of Future Earth serves as a convener that helps US researchers engage in research based on the co-design and co-production of knowledge and tools designed to help develop solutions to global environmental challenges such as fresh water security, coastal vulnerability, disaster risk reduction and resilience. The program is supported by major U.S. agencies, under the interdisciplinary auspices of the U.S. Global Change Research Program. Over the past several years, the US Hub has taken on activities that directly support the USGCRP and its member agencies. These funds will be used to further engage the US research community in these developing efforts.
The Future Earth program is organized around three major themes: Dynamic Planet; Global Development; and Transformations toward Sustainability. Under the auspices of these three themes, the US Hub of the Future Earth Secretariat will support workshops and other efforts to foster the co-design of research to enhance transdisciplinary efforts to help develop solutions for many challenging societal issues. The US Hub will also develop programs and initiatives to educate the next generation of inter-disciplinary researchers and professionals on how to integrate global sustainability with human prosperity and will actively engage the public through an extensive communication and outreach effort.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF COLORADO, THEUniversity of Colorado at BoulderJoshua J Tewksbury(206) 616-2129jote0936@colorado.edu09/17/2018$1,011,401$381,00510/01/201809/30/2021GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITResearch Capacity Building and Communication Activity Support for Future Earth1755526007431505007431505COLLABORATIVE RESEARCHAnne L. Emig(703) 292-8710aemig@nsf.gov3100 Marine Street, Room 481BoulderCO80303-1058BoulderUS02University of Colorado Boulder3100 Marine, Room 457BoulderCO80303-1058BoulderUS02This award provides core support for capacity building, communications and information technology activities of the US Hub of Future Earth Secretariat. The Future Earth program seeks to coordinate international global change research to help accelerate transformations to sustainability through research and innovation. In this role, the US Hub of Future Earth serves as a convener that helps US researchers engage in research based on the co-design and co-production of knowledge and tools designed to help develop solutions to global environmental challenges such as fresh water security, coastal vulnerability, disaster risk reduction and resilience. The program is supported by major U.S. agencies, under the interdisciplinary auspices of the U.S. Global Change Research Program. Over the past several years, the US Hub has taken on activities that directly support the USGCRP and its member agencies. These funds will be used to further engage the US research community in these developing efforts.
The Future Earth program is organized around three major themes: Dynamic Planet; Global Development; and Transformations toward Sustainability. Under the auspices of these three themes, the US Hub of the Future Earth Secretariat will support workshops and other efforts to foster the co-design of research to enhance transdisciplinary efforts to help develop solutions for many challenging societal issues. The US Hub will also develop programs and initiatives to educate the next generation of inter-disciplinary researchers and professionals on how to integrate global sustainability with human prosperity and will actively engage the public through an extensive communication and outreach effort.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF TEXAS AT AUSTINUniversity of Texas at AustinChristian Claudel(512) 705-7195christian.claudel@utexas.eduPeter H Stone, Stephen D Boyles09/17/2018$621,579$384,24010/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: Medium: Collaborative Research: Synergy: Augmented reality for control of reservation-based intersections with mixed autonomous-non autonomous flows1739964170230239042000273CYBER-PHYSICAL SYSTEMS (CPS)Ralph Wachter(703) 292-2653rwachter@nsf.gov3925 W Braker Lane, Ste 3.340AustinTX78759-5316AustinUS10University of Texas at AustinTX78712-1532AustinUS25In urban environments, signalized intersections are a major cause of congestion since their actual capacity is very low. Autonomous vehicles are a possible leap forward: by receiving coordinated guidance information from the intersection system itself, these vehicles could navigate through the intersections with minimal speed reduction or wait times, resulting in far more efficient intersections. These smart intersections can reduce wait times by orders of magnitude, though they only work if all vehicles are autonomous: the presence of even one percent of non-autonomous vehicles would negate almost all benefits. This project investigates augmented reality technology as a scalable means of improving flow through these smart intersections by coordinating human driven vehicles with autonomous vehicles, maximizing intersection throughput while minimizing collision risks. This research will benefit the U.S. economy by providing an inexpensive, scalable way of reducing congestion without the need to ban human-driven forms of transport (pedestrians, bicycles), and without the cost of having only autonomous vehicles. This research is at the interface of several disciplines including transportation engineering, control theory and human factors.
The guidance of human-driven vehicles is critical to improve the capacity of future smart intersections safely. While these intersections show considerable potential benefit in a fully automated world, their performance strongly degrades if even a few vehicles are human-driven. Given a high penetration of augmented reality devices (smart glasses), and measurement data from human-driven and autonomous vehicles, including the predicted paths of autonomous vehicles, can human-driven vehicles be guided through a smart intersection as quickly and safely as possible? The answer requires one to simultaneously solve real-time estimation and control problems, in a dynamic environment, with uncertain actuation given the performance of humans. The project develops efficient algorithms to learn the expected performance of each driver. The routing of vehicles in a reservation-based intersection system takes into account human behavior and the physical limitations of vehicles. Strategies are developed to effectively communicate guidance information to drivers in a mixed-reality setting. These results will be validated on an experimental setup involving vehicles driven by humans and equipped with augmented reality devices. This project is jointly supported with the Department of Transportation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF WASHINGTONUniversity of WashingtonLinda N Boyle(206) 616-0245linda@uw.edu09/17/2018$226,412$110,00010/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: Medium: Collaborative Research: Augmented reality for control of reservation-based intersections with mixed flows1739085605799469042803536CYBER-PHYSICAL SYSTEMS (CPS)Ralph Wachter(703) 292-2653rwachter@nsf.gov4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07University of Washington4333 Brooklyn Ave NESeattleWA98195-0001SeattleUS07In urban environments, signalized intersections are a major cause of congestion since their actual capacity is very low. Autonomous vehicles are a possible leap forward: by receiving coordinated guidance information from the intersection system itself, these vehicles could navigate through the intersections with minimal speed reduction or wait times, resulting in far more efficient intersections. These smart intersections can reduce wait times by orders of magnitude, though they only work if all vehicles are autonomous: the presence of even one percent of non-autonomous vehicles would negate almost all benefits. This project investigates augmented reality technology as a scalable means of improving flow through these smart intersections by coordinating human driven vehicles with autonomous vehicles, maximizing intersection throughput while minimizing collision risks. This research will benefit the U.S. economy by providing an inexpensive, scalable way of reducing congestion without the need to ban human-driven forms of transport (pedestrians, bicycles), and without the cost of having only autonomous vehicles. This research is at the interface of several disciplines including transportation engineering, control theory and human factors.
The guidance of human-driven vehicles is critical to improve the capacity of future smart intersections safely. While these intersections show considerable potential benefit in a fully automated world, their performance strongly degrades if even a few vehicles are human-driven. Given a high penetration of augmented reality devices (smart glasses), and measurement data from human-driven and autonomous vehicles, including the predicted paths of autonomous vehicles, can human-driven vehicles be guided through a smart intersection as quickly and safely as possible? The answer requires one to simultaneously solve real-time estimation and control problems, in a dynamic environment, with uncertain actuation given the performance of humans. The project develops efficient algorithms to learn the expected performance of each driver. The routing of vehicles in a reservation-based intersection system takes into account human behavior and the physical limitations of vehicles. Strategies are developed to effectively communicate guidance information to drivers in a mixed-reality setting. These results will be validated on an experimental setup involving vehicles driven by humans and equipped with augmented reality devices. This project is jointly supported with the Department of Transportation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.WOODS HOLE OCEANOGRAPHIC INSTITUTIONWoods Hole Oceanographic InstitutionHenry J Dick(508) 289-2590hdick@whoi.eduMasako Tominaga09/17/2018$639,792$639,79210/01/201809/30/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Thin Crust Over the Marion Rise: Remelting the Gondwanan Mantle1657983001766682001766682MARINE GEOLOGY AND GEOPHYSICSBarbara L. Ransom(703) 292-8581bransom@nsf.gov183 OYSTER POND ROADWOODS HOLEMA02543-1041Woods HoleUS09Woods Hole Oceanographic InstitutionMA02543-1041Woods HoleUS09It has long been assumed that the Earth consists of a thin, outer, silica-rich, hardened crust overlying a thick layer of silica-poor, magnesium-rich, mantle rock known as peridotite and an inner, nickel-iron core. Compared to Earth's ~40 kilometer thick continental crust, ocean crust is generally considered to be relatively thin (i.e., 6-7 km thick). One of the most exciting discoveries in ocean sciences over the last 15 years has been the discovery that parts of the seafloor do not have normal ocean crust, but rather Earth's mantle is exposed directly on the seafloor over large regions of the Arctic, Indian, and Atlantic Oceans. Just how much of the seafloor is exposed mantle not presently known, although estimates have been made that predict up to 25%. This research comprises the US portion of a two-ship, US-German, collaborative project designed to map, collect gravity and magnetic geophysical data, and sample a large areas of the seafloor along the Southwest Indian Ridge in the western Indian Ocean to determine how much mantle rock is exposed there. Geophysical data and geochemical analysis of major and trace elements and various isotopes will be carried out post-cruise at shore-based laboratories. The results of this work, combined with ongoing French studies on the eastern portion of the southwest Indian Ridge will allow, for the first time, an accurate estimate of how much mantle is exposed along an entire mid-ocean ridge. More than 80% of this region has never been mapped and sampling has been largely restricted to a few sections of a narrow 3-mile-wide rift valley that forms the southwest Indian Ridge mid-ocean ridge spreading center. This work is important because mantle rock is very unstable at the Earth's surface, particularly on the seafloor where it is exposed to and extensively reacts with seawater. These reactions produce hydrogen and methane, which, in turn, provide energy for bacterial life in the deep sea and support what could be an extensive biomass below the seafloor that is presently not accounted for in the inventory of life supported by our planet. The reactions between seawater and mantle rock also potentially sequester carbon in the form of carbonate minerals that form by the removal of CO2 from seawater, thereby affecting global and atmospheric carbon budgets at different time scales. Broader impacts of the work include training of graduate students at three institutions, support of an early career scientist from a gender under-represented in the sciences, outreach to elementary and high schools, and public outreach. This project takes to sea a high school teacher and a scientific blogger, who will conduct live interaction sessions with students during the oceanographic expedition and who will prepare age-appropriate educational materials and radio documentaries of the research and oceanographic cruise. There is also a significant component of international collaboration with German, Italian, and Chinese scientists some of whom will participate in the expedition and interact closely with the students and US faculty, further building international relations with these scientific communities.
This research consists of an oceanographic expedition to the crest of the Marion Rise on the Southwest Indian Ridge to test the hypothesis that that the Marion Rise is supported by lateral mantle heterogeneity produced by the recycling different Gondwanan mantle provinces beneath the modern ocean ridge, as opposed to a thermal anomaly due to a mantle plume. This is the first leg of a two-leg US-German-Chinese international program to study the Marion platform, a little studied part of the seafloor, and its origin. The cruise will use multibeam sonar to map the seafloor in the area, will dredge rocks for later shore-based laboratory analysis, collect gravity and magnetic geophysical data, and carry out geochemical analyses of select samples. Sea surface magnetics will be used to locate central magnetic anomalies to identify spreading centers and determine spreading rate asymmetries. Regions of a amagmatic seafloor spreading will be determined by their weak magnetic signal and lack of easily definable magnetic lineations. Gravity surveys will allow calculation of residual mantle Bouguer anomalies from which magmatically robust regions can be identified on the basis of their characteristic negative lows. In addition to on-axis work, the expedition will include extensive off-axis dredging to help delineate mantle domains and major magmatic centers. Post-cruise research includes petrographic and geochemical analysis of collected seafloor basalts and peridotites to determine the nature and origin of the mantle source in the Marion Rise area. Chinese collaborators will conduct major and trace element analyses of dredged rocks and US laboratories will analyze the isotopes and isotopic ratios of Hf, and Os as well as radiogenic isotopes of Sr, Nd, and Pb. Calculation of the mantle using geochemically determined mantle density gradients will estimate the extent of serpentinization in the exposed mantle sections. This, together with processed magnetization data, lithologic analysis of collected rock samples, and multi-channel sonar bathymetry will be used to construct a geologic map of the area to determine the tectonic evolution and crustal architecture of the Platform. This work fills a significant sampling gap on mid-ocean ridges and will enhance significantly our understanding of global mantle variability as well as provide new insights into the nature of shallow mantle convection and on the origin of mantle hotspots.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF THE COLORADO SCHOOL OF MINESColorado School of MinesSoutir Bandyopadhyay(303) 273-3677sbandyopadhyay@mines.edu09/17/2018$55,941$55,94110/01/201807/31/2019GrantNSF4900490047.049040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Theory and Methods for Massive Nonstationary and Multivariate Spatial Processes1854181010628170010628170STATISTICSGabor J. Szekely(703) 292-8869gszekely@nsf.gov1500 IllinoisGoldenCO80401-1887GoldenUS07Colorado School of Mines1500 Illinois StreetGoldenCO80401-1887GoldenUS07The field of spatial statistics is an expanding subset of statistical science with numerous applications in a wide variety of specialties such as geophysical, environmental, ecological and economic sciences. Modern datasets in these sciences often involve multiple variables observed at thousands to millions of irregularly spaced geographical locations. Associated scientific goals include surface estimation, stochastic simulation and statistical modeling to gain insight of underlying phenomena. Statistical analyses require flexible nonstationary and multivariate constructions, which have heretofore been hampered by a lack of models adequate for datasets of large magnitude. This project addresses this gap in statistical science, developing a unifying framework for nonstationary and multivariate spatial models capable of modeling complex spatial dependencies. Additionally, the justification for the use of nonstationary models is generally relegated to empirical results with data and simulation experiments; this research will develop a companion theory for exploring the relative benefit of these more complex spatial models. Using the tools introduced in this project, the final major goal is to develop a gridded data product for the historical climate of the United States based on large, irregularly spaced observational networks with transparent statistical methodology and formal quantification of the uncertainty in such an analysis. Historical data products such as this are of crucial importance in the fields of atmospheric and climate sciences.
Modern spatial statistics has increased focus on developing methods for massive spatial datasets that involve multiple variables with complex dependency structures. This research aims to foster a common framework via multiresolution processes for modeling nonstationary and multivariate spatial structures that does not break down in the face of large sample sizes. Multiresolution processes lend themselves to fast estimation and computation, and also to the linked theoretical questions of asymptotic behavior of spatial estimators. For example, there is a lack of rigorous theoretical treatment of nonstationary approaches, with current understanding limited to experimental results. The companion large sample theory of this research is aimed at identifying situations in which nonstationary models provide tangible benefits over simpler stationary cousins. A linked goal is approximation theory for existing spatial constructions; special multiresolution constructions can approximate existing covariances such as the Matern, allowing for a theoretical treatment of spatial smoothing under these common classes of covariances. Additionally, the project will generalize the notion of a multiresolution process to the multivariate setting, allowing for feasible and flexible inference-based modeling of massive multivariate spatial datasets.G & A TECHNICAL SOFTWARE INCG & A Technical Software, Inc.Thomas Lund(303) 415-9701lund@cora.nwra.com09/17/2018$120,089$40,26109/01/201806/30/2021GrantNSF4900490047.050040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Modeling the Nonlinear Dynamics of Deep Gravity Waves in the Mesosphere and Thermosphere1853000048004688048004688AERONOMYIlia I. Roussev(703) 292-8519iroussev@nsf.gov11864 Canon BlvdNewport NewsVA23606-4253Newport NewsUS03G & A Technical Software, Inc.11864 Canyon BlvdNewport NewsVA23606-4223Newport NewsUS03Gravity Waves (GW) in the Earth's atmosphere exhibit highly diverse dynamics and they have multiple effects throughout the atmosphere. These waves are believed to be the main driver of the Mesosphere and Lower Atmosphere (MLT) region, which is why they are a subject of active research and debate by the Aeronomy community in the U.S. The GW also influence a wide range of other physical processes ranging from tidal and planetary wave structures and dynamics to minor species transport and plasma dynamics in the ionosphere. Therefore, the need to describe such effects accurately also has broader implications for modeling climate variations, responses to variable solar forcing, and space weather, among others. The main purpose of this three-year project is to investigate in great detail the three-dimensional structure and dynamics of GW by means of state-of-the-art numerical simulations. The research project will also provide a significant research opportunity for a graduate student in Aeronomy. The research and EPO agenda of this project supports the Strategic Goals of the AGS Division in discovery, learning, diversity, and interdisciplinary research.
It is well established that GW play an important role throughout the upper atmosphere of the Earth. These waves, however, are very difficult to model directly due to their small spatial scales. That leads to the use of GW parameterization in global models. This three-year project will utilize a finite-volume simulation code to solve the compressible, or an-elastic three-dimensional non-linear Navier-Stokes equations in simulations of GW. The project team will investigate numerically the following critical scientific questions: (i) how does GW's spatial and temporal distribution influence GW's self-acceleration instability, dissipation, mean forcing, and penetration to thermosphere ionosphere?; (ii) what role do wave-wave interactions, mean wind, and stability play in GW evolution?; and, (iii) what are the key dynamics in GW-tidal interactions influencing MLT and Thermosphere-Ionosphere dynamics?
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MICHIGAN STATE UNIVERSITYMichigan State UniversityMichael R O'Rourke(517) 355-4490orourk51@msu.eduMarisa Rinkus, Stephanie E Vasko09/17/2018$71,909$71,90910/01/201809/30/2019GrantNSF4900490047.079040100 NSF RESEARCH & RELATED ACTIVITToolbox Workshop for the AccelNet PI Meeting1844794193247145AccelNet - Accelerating ResearClaire Hemingway(703) 292-7135chemingw@nsf.govOffice of Sponsored ProgramsEast LansingMI48824-2600East LansingUS08Michigan State UniversityMI48824-2600East LansingUS08The ability to communicate and collaborate is key to effective research teams and networks. This project focuses on enhancing this ability through a dialogue-based workshop to be held in Washington DC for newly funded members of international network-to-network collaborations as part of an awardee project meeting. The workshop builds on a decade of work by the Toolbox Dialogue Initiative to design and deliver evidence-based facilitated discussions that increase the communicative and collaborative capacity of cross-disciplinary teams. The workshop will advance knowledge along two fronts. First, the reflective discussion among participating members of the networks of networks will increase their own understandings of potential obstacles to project success and opportunities for project development. Second, the extension of the facilitative approach from research teams to larger, distributed networks of networks will provide new insights to science collaborations.
The primary goal of this workshop is to provide members of international network-to-network collaborations the opportunity to examine beliefs and values that inform their contributions as collaborators, researchers, and networks members. Workshop participants will represent newly funded projects in the Accelerating Research through International Network-to-Network Collaboration program. The workshop will be crafted for each network represented, maximizing the value of the time they spend in dialogue. The workshop will generate: (1) a team-focused conversation about the conceptual foundations of their project that can coordinate their collective thinking going forward; (2) products of a co-creation activity that will contribute to the team's process; (3) a report that offers communication and collaboration recommendations for the team's consideration; (4) a communication-focused survey tool that the teams can use to check in periodically about the status of their collaboration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.TRUSTEES OF THE UNIVERSITY OF PENNSYLVANIA, THEUniversity of PennsylvaniaLEE BASSETT(215) 573-7565lbassett@seas.upenn.eduRashid Zia, Firooz Aflatouni09/17/2018$750,000$750,00010/01/201809/30/2021GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITRAISE-EQuIP: Chip-Scale Quantum Memories for Practical Quantum Communication Networks1842655042250712042250712COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.govResearch ServicesPhiladelphiaPA19104-6205PhiladelphiaUS02University of Pennsylvania3451 Walnut StreetPhiladelphiaPA19104-6205PhiladelphiaUS02RAISE-EQuIP: Chip-Scale Quantum Memories for Practical Quantum Communication Networks
This project is conceived in the context of the NSF's call for Research Advanced by Interdisciplinary Science and Engineering (RAISE), and specifically a Dear Colleague Letter for Engineering Quantum Integrated Platforms for Quantum Communication (EQuIP). It addresses a grand challenge of 21st-century science: leveraging modern capabilities in materials science, nanofabrication, signal processing, and integrated systems-on-a-chip to harness the computational power and sensitivity of quantum-coherent systems for practical applications. Motivated by the clear potential of spin-based quantum devices, this RAISE-EQuIP project adopts an engineering approach to address a series of technological roadblocks that currently limit their performance and scalability. The interdisciplinary approach harnesses state-of-the-art classical and quantum signal processing, electronic circuit design in silicon-based integrated platforms, machine learning optimization, and nanophotonic design, with the aim to transform spin-based quantum registers from a laboratory-scale experiments into compact, integrated systems that are available to power new applications and scientific investigations. With superior performance offered under real-world constraints, these devices can be deployed in testbed quantum communication networks and will enable future investigations of fundamental quantum physics. The collaborative project will engage many undergraduate and graduate students from diverse backgrounds; its research goals are coupled with a broad educational mission to educate students and the public about the emerging field of quantum science and technology. Through the realization of compact, robust, low-cost quantum devices, this project will support the design and deployment of hands-on activities for K-12 students and the public about spins, photons, and quantum communication, for use at venues that target large, diverse populations in Philadelphia, PA and Providence, RI.
Clusters of nuclear spins coupled to an optically addressable electron-spin qubit such as the nitrogen-vacancy (NV) center in diamond are leading platforms for quantum communication. The cluster constitutes a register of qubits that can be individually addressed, entangled, stored for times exceeding 1s, and utilized for quantum error correction. However, state-of-the-art experiments are currently performed on laboratory-scale setups consisting of customized optical cryostats, vibration-sensitive free-space optics, and racks of microwave electronics. Performance is further impeded by sub-optimal photon collection efficiency and labor-intensive calibration requirements for quantum control sequences. This RAISE-EQuIP project will tackle these challenges on multiple levels, drawing on complementary expertise of the collaborating researchers in diamond NV quantum control and device engineering (Bassett), high-speed analog circuit design and signal processing (Aflatouni), and computational physics and nanophotonics (Zia). We will design and build compact, fiber-coupled diamond devices featuring nanofabricated optical metalenses and impedance-matched microwave antennas to transmit optical and spin-resonance signals, respectively, and integrate these devices with custom-fabricated silicon CMOS chips that process the necessary analog and digital signals for spin resonance, photon counting, and real-time adaptive feedback control. Computational machine learning methods will enable efficient mapping and control of the unknown coupled-spin Hamiltonian. The resulting quantum-register devices will exhibit performance superior to state-of-the-art laboratory systems, but with a fraction of the size, cost, and energy requirements. Components of the modular, hybrid-integrated system are generalizable to other quantum architectures based on spins, ions, photons, and superconducting qubits, so these devices can serve as a framework for future generations of portable quantum technologies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.REGENTS OF THE UNIVERSITY OF CALIFORNIA, THEUniversity of California-BerkeleyAlexandra von Meier(707) 322-3538vonmeier@berkeley.edu09/17/2018$299,325$299,32510/01/201809/30/2023GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITFW-HTF: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency1840083124726725071549000FW-HTF: Advancing Cognitive anDavid Corman(703) 292-8950dcorman@nsf.govSponsored Projects OfficeBERKELEYCA94704-5940BerkeleyUS13California Institute for Energy and Environment2087 Addison Street, Second FlooBerkeleyCA94704-1268BerkeleyUS13The Future of Work at the Human-Technology Frontier (FW-HTF) is one of 10 new Big Ideas for Future Investment announced by the National Science Foundation. The FW-HTF cross-directorate program aims to respond to the challenges and opportunities of the changing landscape of jobs and work by supporting convergent research. This award fulfills part of that aim. Effective decision making by power grid operators in extreme events (e.g., Hurricane Maria in Puerto Rico, the Ukraine cyber attack) depends on two factors: operator knowledge acquired through training and experience, and appropriate decision support tools. Decision making in electric grid operation during extreme adverse events directly impacts the life of citizens. This project will augment the cognitive performance of human operators with new, human-focused decision support tools and better, data-driven training for managing the grid especially under highly disruptive conditions. The development of new generation of tools for online knowledge fusion, event detection, cyber-physical-human analysis in operational environment can be applied during extreme events and provide energy to critical facilities like hospitals, city halls and essential infrastructure to keep citizens safe and avoid economic loss for the Nation. Higher performance of operators will improve worker quality of life and will enhance the economic and social well-being of the country. The project's training objectives will leverage existing educational efforts and outreach activities and we will publicize the multidisciplinary outcomes through multiple venues.
The proposed project will integrate principles from cognitive neuroscience, artificial intelligence, machine learning, data science, cybersecurity, and power engineering to augment power grid operators for better performance. Two key parameters influencing human performance from the dynamic attentional control (DAC) framework are working memory (WM) capacity, the ability to maintain information in the focus of attention, and cognitive flexibility (CF), the ability to use feedback to redirect decision making given fast changing system scenarios. The project will achieve its goals through analyzing WM and CF and performance of power grid operators during extreme events; augmenting cognitive performance through advanced machine learning based decision support tools and adaptive human-machine system; and developing theory-driven training simulators for advancing cognitive performance of human operators for enhanced grid resilience. A new set of algorithms have been proposed for data-driven event detection, anomaly flag processing, root cause analysis and decision support using Tree Augmented naive Bayesian Net (TAN) structure, Minimum Weighted Spanning Tree (MWST) using the Mutual Information (MI) metric, and unsupervised learning improved for online learning and decision making. Additionally, visualization tools have been proposed using cognitive factor analysis and human error analysis. We propose a training process driven by cognitive and physiometric analysis and inspired by our experience in operators training in multiple domain: the power grid, aircraft and spacecraft flight simulators. A systematic approach for human operator decision making is proposed using quantifiable human and engineering analysis indices for power grid resiliency.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF FLORIDAUniversity of FloridaJoel B Harley(732) 567-6786joel.harley@ufl.edu09/17/2018$273,118$273,11810/01/201809/30/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITEAGER: Real-Time: Ultrasonic Reconstruction and Localization with Deep Helmholtz Networks1839704969663814159621697COMMS, CIRCUITS & SENS SYSAkbar Sayeed(703) 292-4753asayeed@nsf.gov1 UNIVERSITY OF FLORIDAGAINESVILLEFL32611-2002GainesvilleUS03University of Florida1 University of FloridaGainesvilleFL32611-2002GainesvilleUS03Ultrasonic Reconstruction and Localization with Deep Helmholtz Networks
This project studies physics-informed neural networks to characterize and monitor materials and engineered systems with ultrasound. Ultrasound is studied because it is a wireless, high resolution, medically safe, and inherently secure technology that is driving innovations in wearables, medical implants, secure / encrypted communication systems, and imaging. The project's neural network algorithms can characterize materials and engineered systems from the micro-level (e.g., micro-electrical-mechanical systems) to the macro-level (e.g., pipelines, airplanes, or rail lines). The neural networks characterize the materials by learning the general behavior of ultrasound from simulated data, physical constraints, and measured data. That learned behavior is then compared with the true measured behavior. To achieve our goal, three significant challenges of applying neural networks (and machine learning generally) to many engineered systems are studied: (1) experimental training data is often scarce or unavailable, (2) data diversity and variability is typically high, and (3) purely data-driven approaches offer few engineering assurances. Data scarcity is addressed by training neural networks with simulations rather than experimental data. Data diversity and variability is addressed by using transfer learning theory to transfer generalized knowledge from the simulation data into the analysis of the experimental data. Engineering assurances are improved by incorporating physics-based constraints into the neural networks. The resulting neural networks are referred to as Helmholtz networks, named for the time-independent wave equation.
The objective of the project is to establish the foundation for Helmholtz networks, which are deep, generative, physics-informed neural networks that reconstruct ultrasonic wave propagation and locate ultrasonic sources. The Helmholtz networks are based on the fact that each frequency of a wave can be represented as the sum of a sparse number of spatial modes. The modes are constrained by the Helmholtz equation and this physical constraint ensures that the machine learning algorithm is trustworthy for system-critical engineered systems (e.g., health monitoring of an aircraft). Such physics-informed machine learning is an important (albeit not widely studied) topic for integrating advanced computation tools into real-time engineered systems.
The research thrusts of this proposal are to initiate and explore the foundations for three new types of neural networks: (1) generative Helmholtz networks to learn modal representations of waves and reconstruct wavefields, (2) localization networks to locate ultrasonic sources under uncertainties, and (3) localization Helmholtz networks to locate sources from learned modal representations. Thrust 1 explores the creation of generative models (i.e., generative Helmholtz networks) that learn the spatial modal characteristics of a medium from simulations. These generative models then reconstruct wavefields from undersampled test data. Thrust 2 studies localization networks to locate ultrasonic sources under simulated uncertainties, such as velocity, delay, and/or amplitude uncertainty. Thrust 3 investigates the use of transfer learning to combine Thrust 1 and Thrust 2 and use the learned modes to locate sources in geometrically complex media.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.ARIZONA STATE UNIVERSITYArizona State UniversityJennifer Blain Christen(480) 965-5479Jennifer.BlainChristen@asu.eduSule Ozev, Jesse Senko09/17/2018$1,000,000$1,000,00001/01/201912/31/2021GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCPS: TTP Option: Medium: Machine learning enabled "smart nets" to optimize sustainable fisheries technologies1837473943360412806345658CYBER-PHYSICAL SYSTEMS (CPS)Ralph Wachter(703) 292-2653rwachter@nsf.govORSPATEMPEAZ85281-6011TempeUS09Arizona State UniversityP.O. Box 876011TempeAZ85287-6011TempeUS09Fisheries employ 260 million people globally and fish are a primary animal protein source for roughly 40% of the world's population. Fishing effort has increased worldwide over the past few decades, leading to concerns over the incidental capture (termed "bycatch") of non-target species, especially endangered species such as sea turtles, sharks, and marine mammals. Globally, bycatch of sea turtles is especially problematic as recent estimates suggest that hundreds of thousands of turtles are killed annually in fishing gear, representing the greatest known threat to their continued survival. This project addresses this problem through cyber-physical system-enabled technologies.
This project builds on an observation about fish behavior that species respond differently to the light spectrum and that can be used to modulate their behaviors. This smart nets project extends that observation to determine signatures for sensing modalities of different species. The intent is to develop fishing gear, specifically fishing nets, that can deter non-target species. The project uses machine learning to determine effective cues, e.g., light and sound that uses the least amount of power possible to prevent an endangered species from capture in the nets without decreasing the fishermen's target catch. Using underwater cameras with standard video, infrared, and sonar to monitor species behavior to various signatures, it builds a database of the responses for each species under varying oceanic environment conditions. The project plans large-scale follow-up studies in partnership with the National Oceanic and Atmospheric Administration (NOAA). This research on CPS technology for the fishing industry will be invaluable to the design of the next-generation of CPS-enabled fishing nets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.MISSISSIPPI STATE UNIVERSITYMississippi State UniversityShelly R Hollis(662) 325-2510shelly.hollis@rcu.msstate.edu09/17/2018$266,496$266,49610/01/201809/30/2020GrantNSF4900490047.070040100 NSF RESEARCH & RELATED ACTIVITCollaborative Research: Identifying Participation Barriers to Computer Science Education in Rural Mississippi1837407075461814075461814STEM + Computing (STEM+C) PartFay Payton(703) 292-8950fpayton@nsf.govPO Box 6156MISSISSIPPI STATEMS39762-9662Mississippi StateUS03Mississippi State UniversityMS39762-9662Mississippi StateUS03The primary goal of the small strand, K-14 project "Collaborative Research: Identifying Participation Barriers to Computer Science Education in Rural Mississippi" is to develop a researcher-practitioner partnership (RPP) to identify barriers to participation in computer science education in high poverty, rural areas of Mississippi. In the past two years, a collaborative effort between the Mississippi Department of Education (MDE) and Mississippi State University's (MSU's) Research and Curriculum Unit (RCU) implemented a statewide computer science pilot offered free of charge to K-12 schools. Entering the third year of the pilot, 74 of 148 school districts in the state are now offering computer science courses; however, it has been observed that districts situated in the most rural, highest poverty, and lowest income areas in the state (primarily the Delta region) are not participating in the opportunity to provide their teachers free computer science professional development and thereby offer students access to courses that would begin preparing them for jobs in a very high-demand, high-salary career. Through a RPP, issues and perceptions will be investigated to determine why these districts are not taking advantage of this opportunity to offer computer science education in the classrooms.
This collaborative project between MSU and Mississippi Valley State University (MVSU), a four-year institution of higher learning located in the Delta, will form a partnership with teachers, administrators, and counselors from six districts in the area surrounding MVSU, as well as the local community college, business owners, community leaders, and parents, to identify issues acting as barriers or constraints to computer science education opportunities. Identifying and addressing the root causes of the lack of participation in these types of demographic and geographic areas will give a voice to those who are most directly involved, while also transforming perceptions of computer science and broadening participation in the field based on contributions from more diverse groups, primarily African American teachers and students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.SPELMAN COLLEGESpelman CollegeAngelino Viceisza(404) 270-6055aviceisz@spelman.edu09/17/2018$299,797$299,79709/15/201808/31/2021GrantNSF4900490047.075040100 NSF RESEARCH & RELATED ACTIVITExcellence in Research: The impact of online comparison websites on the remittance industry1832144069174407069174407ECONOMICSKwabena Gyimah-Brempong(703) 292-7466kgyimahb@nsf.gov350 Spelman Lane SWAtlantaGA30314-4399AtlantaUS05Spelman CollegeGA30314-4399AtlantaUS05This proposed research project will use experimental methods and surveys to investigate the effects of on-line comparison shopping on choice of companies and fees charged for migrants sending money to their home countries. Even though migrant remittances serve as an important source of financial flows to the developing world, hence a major source of economic growth and global development, the cost of remittances tend to be very high averaging about 8% of the amount transmitted. It is hypothesized that on-line comparison shopping will allow consumers to choose companies that provide lower cost with better services and as a result, prices for these services are likely to fall. While this is a possibility, there is limited empirical evidence of this issue mainly because of lack of data. The proposed research will combine economic theory, structural modelling, field experiments, and survey data to investigate these issues. The PIs will survey 400 migrants from different countries who use these on-line comparison shopping websites to determine what impacts on-line comparison shopping have on choice of company and the impact of these comparisons on the cost of sending money. The results of this research will have important impacts on the cost of sending migrant remittances, possibly increase the volume and the number of market participants, as well as significantly contribute to global development. The results will also establish the US as the global leader in migrants' transfer markets.
This proposed research project will use a variety of methods to study the causal impacts of on-line comparison shopping for migrant remittance services on the choice of companies by migrants and the cost of such services. This study will be one of the first to attempt a rigorous assessment of the causal impact of comparison websites on both the demand and supply sides of the industry by combining (1) theory, (2) field experiments, (3) survey data, (4) structural modeling, and (5) policy evaluations. The PIs seek to extend research on the impacts of information and communication technologies on consumer behavior to an unexplored market---the remittance industry. By surveying a sample of 400 migrants at multiple points in time and exposing them to randomized information treatments, the PIs will identify the causal impact of "price comparison" on migrant choices. The PIs will then use a structural model to conduct counterfactual policy evaluations to assess the potential supply-side impacts as well as welfare effects of these on-line comparison shopping experiments. The findings of this research will inform the policy debate surrounding ways to reduce cost in the migrant remittance industry.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.INSPIRIT IOT, INC.Inspirit IoT, Inc.Kyle J Rupnow(217) 778-6116kjrupnow@gmail.com09/17/2018$750,000$750,00009/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: Efficient Custom Machine Learning for Embedded Intelligence in the Internet of Things1831263080221749SMALL BUSINESS PHASE IIRichard Schwerdtfeger(703) 292-8353rschwerd@nsf.gov2510 Hallbeck Dr.ChampaignIL61822-6879ChampaignUS13Inspirit IoT, Inc.60 Hazelwood Dr.ChampaignIL61820-7460ChampaignUS13The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will result in a significant improvement in the performance, power, and cost of deploying machine learning (ML) solutions through horizontal platform technologies that enable many vertical applications. This improvement will accelerate deployment of intelligent systems and improve scalability through localized intelligence. Our technology automates hardware design, implementation, and deployment to Field-Programmable Gate Array (FPGA) platforms. Our initial target verticals: Security and Surveillance, Predictive Maintenance, and Healthcare represent hundreds of billions USD in growth markets for IoT devices and substantially more economic impact through improved efficiency in deployment and operations and reduced societal costs. Improved performance, power consumption and scalability of these key technologies will lead to improved public safety, improved intelligence in home healthcare services, and more efficient manufacturing and energy systems through deployment of Predictive Maintenance technologies on key industrial equipment. Wide deployment of these technologies will lead to substantial energy savings and a corresponding reduction in carbon emissions, reduced economic loss due to negative events, improved scalability and response time to predicted or active negative events, and lower cost in deployment and operations due to low cost, low power, and physically small sensor systems.
The proposed project focuses on design of high performance, energy-efficient platforms for ML applications, and associated design tools and libraries. Neural networks are heavily used for many machine learning problems but optimizing for efficient deployment currently requires extensive trial-and-error for the large design space of options. Our deep neural network (DNN) optimization framework applies bit-width optimizations, weight sharing and pruning automatically to reduce computation and weight storage demands by more than 10X, while analyzing quality of results impact and using fine-tuned retraining to minimize or eliminate accuracy degradation. Our high level synthesis (HLS) tool then translates optimized networks to hardware while applying pipelining, functional unit parallelism, resource sharing, and platform-specific optimizations. Together these tools automate and accelerate the process of analyzing, optimizing and implementing ML for hardware deployment, reducing time and required expertise for hardware design. Our deployment platforms are modular, composable platforms for small, low-cost deployments of audio/video signal processing, feature extraction and classification, systems control (e.g. pan-tilt-zoom cameras), and communications to decision-making or cloud services. We will extend competitive advantages from our Phase I project with features for solutions in the security/surveillance, predictive maintenance, and healthcare verticals, and tight integration of platforms, tools and IP libraries.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.AUTONOMOUS HEALTHCARE INCAutonomous Healthcare IncBehnood Gholami(347) 774-1617bgholami@autonomoushealthcare.com09/17/2018$746,668$746,66809/15/201808/31/2020GrantNSF4900490047.041040100 NSF RESEARCH & RELATED ACTIVITSBIR Phase II: A Clinical Decision Support System for Fluid Resuscitation of Intensive Care Unit Patients1831225078572678SMALL BUSINESS PHASE IINancy Kamei(703) 292-7236nkamei@nsf.gov132 Washington StHobokenNJ07030-4692HobokenUS08Autonomous Healthcare Inc132 Washington St, Ste 305HobokenNJ07030-4692HobokenUS08The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project involves addressing complexities in fluid management, one of the most important issues in critical care. Suboptimal fluid management results in many complications such as pulmonary edema. Studies show that fluid overload is associated with higher rates of morbidity and mortality. Recent studies also show that restrictive fluid resuscitation protocols result in a reduction of mechanical ventilation days and hospital length of stay. The clinical literature provides ample evidence of optimized fluid therapy benefits for different patient populations including those with sepsis and post-operative patients. However, implementation of fluid therapy is highly subjective. Specifically, the most critical unanswered questions involve the timing and the volume of fluid infusions.
This Small Business Innovation Research Phase II project proposes to develop a system which uses continuous measurements from a standard intensive care unit hemodynamic monitoring device to provide actionable feedback for clinicians to optimize fluid and vasoactive drug management. In the proposed Phase II work, we will further develop the clinical decision support system developed in Phase I. This includes further development of the underlying technology and also performing preliminary clinical studies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.UNIVERSITY OF UTAH, THEUniversity of UtahSteven M Blair(801) 585-6157blair@ece.utah.eduBerardi Sensale-Rodriguez, Roseanne Warren, Alonso P Moreno, Christopher Reiche09/17/2018$615,815